Plot

EDA Plot for each crop data

plot_fao_data(data_fao)

## [1] "Adding columns for year and week"
## [1] "Adding columns for year and month"

linear reg for yield VS EHF 95

Abbotsford weekly

## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -27837  -6474  -1373   4047  41932 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 247624.160  53497.038   4.629  0.00169 **
## Week_1       -2171.531   3826.707  -0.567  0.58596   
## Week_2       -2744.458   2644.290  -1.038  0.32968   
## Week_3        3641.847   3466.401   1.051  0.32413   
## Week_4        3003.179   6048.615   0.497  0.63289   
## Week_5        1178.247   3445.783   0.342  0.74121   
## Week_6       -8750.445   4915.786  -1.780  0.11294   
## Week_7        4885.760   6409.091   0.762  0.46775   
## Week_8        5235.628   4971.863   1.053  0.32308   
## Week_9        1747.502   4600.510   0.380  0.71394   
## Week_10      -3484.455   4713.238  -0.739  0.48086   
## Week_11      -7730.497   6721.097  -1.150  0.28329   
## Week_12      -5157.226   4302.043  -1.199  0.26491   
## Week_13       3554.688   4929.279   0.721  0.49136   
## Week_14       2938.131  10286.955   0.286  0.78243   
## Week_15      11179.958   7376.340   1.516  0.16808   
## Week_16          1.334   3193.296   0.000  0.99968   
## Week_17      -3851.450   4653.844  -0.828  0.43190   
## Week_18       4466.951   3566.116   1.253  0.24572   
## Week_19       3144.828   2232.205   1.409  0.19654   
## Week_20       7169.321   4975.559   1.441  0.18758   
## Week_21      -1530.657   4360.146  -0.351  0.73461   
## Week_22      -3232.952   2740.419  -1.180  0.27200   
## Week_23      -2143.645   4251.514  -0.504  0.62771   
## Week_24       5438.291   4307.202   1.263  0.24229   
## Week_25      -7676.930   5358.130  -1.433  0.18982   
## Week_26        777.006   1478.901   0.525  0.61356   
## Week_27       7691.774   4315.853   1.782  0.11257   
## Week_28       3580.131   4283.071   0.836  0.42748   
## Week_29      -1154.881   3714.927  -0.311  0.76384   
## Week_30       2083.311   2774.364   0.751  0.47421   
## Week_31       5982.369  12198.921   0.490  0.63702   
## Week_32      -5687.078   3614.449  -1.573  0.15427   
## Week_33      -8240.645   5629.085  -1.464  0.18137   
## Week_34      27195.753   9710.787   2.801  0.02318 * 
## Week_35      -8417.524   5877.329  -1.432  0.18998   
## Week_36       8261.557   6418.785   1.287  0.23405   
## Week_37      -1111.867  10587.008  -0.105  0.91894   
## Week_38      -3434.407   6234.828  -0.551  0.59678   
## Week_39       -773.375   5236.137  -0.148  0.88623   
## Week_40      -6421.768   8470.863  -0.758  0.47013   
## Week_41      -8203.312   7828.657  -1.048  0.32533   
## Week_42      11641.966   6518.586   1.786  0.11193   
## Week_43     -12452.499   8075.365  -1.542  0.16164   
## Week_44       2689.081   6051.644   0.444  0.66856   
## Week_45     -14715.632   9651.161  -1.525  0.16583   
## Week_46      16405.115   9062.185   1.810  0.10784   
## Week_47      -4234.774   4100.397  -1.033  0.33192   
## Week_48       2209.198   5307.865   0.416  0.68820   
## Week_49       6830.131   5089.663   1.342  0.21645   
## Week_50      -7680.498   5335.802  -1.439  0.18799   
## Week_51      -3394.036   3890.915  -0.872  0.40846   
## Week_52       2109.363   6764.758   0.312  0.76315   
## Week_53      -2308.067   4283.919  -0.539  0.60471   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 36040 on 8 degrees of freedom
## Multiple R-squared:  0.9491, Adjusted R-squared:  0.6122 
## F-statistic: 2.817 on 53 and 8 DF,  p-value: 0.06071

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##  -4213  -1125    -84   1147   4983 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 41267.00    7396.44   5.579 0.000523 ***
## Week_1        159.50     529.08   0.301 0.770741    
## Week_2       -459.92     365.60  -1.258 0.243872    
## Week_3        331.46     479.26   0.692 0.508751    
## Week_4        490.41     836.27   0.586 0.573763    
## Week_5        -86.59     476.41  -0.182 0.860296    
## Week_6      -1051.44     679.65  -1.547 0.160443    
## Week_7        165.41     886.11   0.187 0.856567    
## Week_8       1309.93     687.40   1.906 0.093157 .  
## Week_9       -566.49     636.06  -0.891 0.399123    
## Week_10       -55.58     651.65  -0.085 0.934121    
## Week_11      -710.73     929.25  -0.765 0.466328    
## Week_12      -301.10     594.79  -0.506 0.626357    
## Week_13        88.47     681.52   0.130 0.899920    
## Week_14       942.56    1422.26   0.663 0.526139    
## Week_15       838.48    1019.84   0.822 0.434803    
## Week_16       -32.46     441.50  -0.074 0.943191    
## Week_17      -828.63     643.43  -1.288 0.233808    
## Week_18       392.15     493.05   0.795 0.449360    
## Week_19       690.71     308.62   2.238 0.055595 .  
## Week_20       718.53     687.91   1.045 0.326784    
## Week_21       112.44     602.83   0.187 0.856675    
## Week_22       -14.73     378.89  -0.039 0.969941    
## Week_23      -736.03     587.81  -1.252 0.245879    
## Week_24       221.83     595.51   0.373 0.719193    
## Week_25      -305.94     740.81  -0.413 0.690462    
## Week_26      -271.02     204.47  -1.325 0.221611    
## Week_27      1663.55     596.71   2.788 0.023635 *  
## Week_28      -404.66     592.17  -0.683 0.513685    
## Week_29       108.40     513.62   0.211 0.838130    
## Week_30       388.34     383.58   1.012 0.340983    
## Week_31      -464.93    1686.61  -0.276 0.789797    
## Week_32        -4.64     499.73  -0.009 0.992819    
## Week_33     -1009.16     778.27  -1.297 0.230892    
## Week_34      2567.53    1342.60   1.912 0.092195 .  
## Week_35     -1308.31     812.59  -1.610 0.146055    
## Week_36      1224.31     887.45   1.380 0.205048    
## Week_37      -470.14    1463.75  -0.321 0.756299    
## Week_38        77.30     862.02   0.090 0.930749    
## Week_39        24.27     723.94   0.034 0.974080    
## Week_40      -432.06    1171.17  -0.369 0.721764    
## Week_41       473.49    1082.38   0.437 0.673353    
## Week_42      1507.43     901.25   1.673 0.132946    
## Week_43      -210.32    1116.49  -0.188 0.855269    
## Week_44      -702.37     836.69  -0.839 0.425586    
## Week_45      -764.99    1334.36  -0.573 0.582193    
## Week_46      1168.18    1252.93   0.932 0.378430    
## Week_47      -548.78     566.92  -0.968 0.361390    
## Week_48       768.53     733.86   1.047 0.325590    
## Week_49       169.41     703.69   0.241 0.815807    
## Week_50      -489.42     737.72  -0.663 0.525710    
## Week_51      -770.43     537.95  -1.432 0.189992    
## Week_52       234.75     935.29   0.251 0.808147    
## Week_53      -289.59     592.29  -0.489 0.638006    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4983 on 8 degrees of freedom
## Multiple R-squared:  0.9163, Adjusted R-squared:  0.3614 
## F-statistic: 1.651 on 53 and 8 DF,  p-value: 0.231

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##  -5994  -1963   -161   1272  10520 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 100208.28   12862.34   7.791 5.28e-05 ***
## Week_1          70.66     920.06   0.077   0.9407    
## Week_2        -280.53     635.77  -0.441   0.6707    
## Week_3        1157.06     833.43   1.388   0.2025    
## Week_4        -113.07    1454.27  -0.078   0.9399    
## Week_5        -179.41     828.47  -0.217   0.8340    
## Week_6       -1901.37    1181.91  -1.609   0.1463    
## Week_7         878.86    1540.94   0.570   0.5841    
## Week_8        1843.94    1195.39   1.543   0.1615    
## Week_9       -1332.39    1106.10  -1.205   0.2628    
## Week_10       1049.61    1133.21   0.926   0.3814    
## Week_11      -2306.89    1615.96  -1.428   0.1913    
## Week_12       -948.67    1034.34  -0.917   0.3859    
## Week_13        697.73    1185.15   0.589   0.5723    
## Week_14       1442.84    2473.30   0.583   0.5757    
## Week_15       1522.11    1773.50   0.858   0.4157    
## Week_16        789.24     767.77   1.028   0.3340    
## Week_17      -1225.56    1118.93  -1.095   0.3053    
## Week_18       1141.85     857.40   1.332   0.2196    
## Week_19        993.73     536.69   1.852   0.1012    
## Week_20       1066.51    1196.28   0.892   0.3987    
## Week_21       -839.57    1048.31  -0.801   0.4463    
## Week_22       -927.81     658.88  -1.408   0.1967    
## Week_23      -1178.51    1022.20  -1.153   0.2822    
## Week_24       1360.14    1035.58   1.313   0.2255    
## Week_25      -2343.97    1288.26  -1.819   0.1063    
## Week_26        269.62     355.57   0.758   0.4700    
## Week_27       3366.10    1037.66   3.244   0.0118 *  
## Week_28       -224.66    1029.78  -0.218   0.8328    
## Week_29       1036.99     893.18   1.161   0.2791    
## Week_30        463.16     667.04   0.694   0.5071    
## Week_31       3845.57    2933.00   1.311   0.2262    
## Week_32      -1285.01     869.03  -1.479   0.1775    
## Week_33       -673.49    1353.41  -0.498   0.6321    
## Week_34       6794.01    2334.77   2.910   0.0196 *  
## Week_35      -2673.52    1413.09  -1.892   0.0951 .  
## Week_36       4127.59    1543.27   2.675   0.0282 *  
## Week_37      -2474.94    2545.44  -0.972   0.3594    
## Week_38       -349.25    1499.05  -0.233   0.8216    
## Week_39       -695.63    1258.93  -0.553   0.5957    
## Week_40      -3333.10    2036.66  -1.637   0.1404    
## Week_41       -613.71    1882.25  -0.326   0.7528    
## Week_42       3909.47    1567.27   2.494   0.0373 *  
## Week_43      -3417.51    1941.57  -1.760   0.1164    
## Week_44        315.47    1455.00   0.217   0.8338    
## Week_45      -4087.96    2320.44  -1.762   0.1161    
## Week_46       4392.16    2178.83   2.016   0.0786 .  
## Week_47       -625.61     985.86  -0.635   0.5434    
## Week_48        956.91    1276.17   0.750   0.4748    
## Week_49       1533.99    1223.71   1.254   0.2454    
## Week_50      -1444.04    1282.89  -1.126   0.2930    
## Week_51      -1701.51     935.50  -1.819   0.1064    
## Week_52       1976.93    1626.46   1.215   0.2588    
## Week_53      -1614.43    1029.99  -1.567   0.1557    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8666 on 8 degrees of freedom
## Multiple R-squared:  0.9698, Adjusted R-squared:  0.7694 
## F-statistic: 4.841 on 53 and 8 DF,  p-value: 0.01152

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5837.8 -1725.3  -198.2  1208.5  7536.9 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 123407.92   10478.35  11.777 2.47e-06 ***
## Week_1         806.42     749.53   1.076   0.3133    
## Week_2         -46.83     517.93  -0.090   0.9302    
## Week_3         899.86     678.96   1.325   0.2216    
## Week_4       -1270.65    1184.73  -1.073   0.3148    
## Week_5         -69.53     674.92  -0.103   0.9205    
## Week_6          86.49     962.84   0.090   0.9306    
## Week_7        -317.43    1255.33  -0.253   0.8068    
## Week_8        -238.38     973.83  -0.245   0.8128    
## Week_9        -164.69     901.09  -0.183   0.8595    
## Week_10        202.39     923.17   0.219   0.8320    
## Week_11       -500.89    1316.45  -0.380   0.7135    
## Week_12       -479.77     842.63  -0.569   0.5847    
## Week_13       -292.09     965.49  -0.303   0.7700    
## Week_14       2049.21    2014.88   1.017   0.3389    
## Week_15       1394.37    1444.79   0.965   0.3628    
## Week_16         81.82     625.46   0.131   0.8991    
## Week_17         44.46     911.54   0.049   0.9623    
## Week_18        -78.92     698.49  -0.113   0.9128    
## Week_19        394.91     437.22   0.903   0.3928    
## Week_20        535.20     974.55   0.549   0.5979    
## Week_21       -553.01     854.01  -0.648   0.5354    
## Week_22       -300.79     536.76  -0.560   0.5906    
## Week_23       -437.69     832.73  -0.526   0.6134    
## Week_24        771.14     843.64   0.914   0.3874    
## Week_25      -1660.72    1049.49  -1.582   0.1522    
## Week_26       -132.08     289.67  -0.456   0.6605    
## Week_27       1726.28     845.34   2.042   0.0754 .  
## Week_28         67.73     838.92   0.081   0.9376    
## Week_29        495.58     727.63   0.681   0.5150    
## Week_30        278.22     543.41   0.512   0.6225    
## Week_31       3385.97    2389.38   1.417   0.1942    
## Week_32        212.87     707.95   0.301   0.7713    
## Week_33      -1152.92    1102.56  -1.046   0.3263    
## Week_34       1066.17    1902.03   0.561   0.5905    
## Week_35        624.93    1151.18   0.543   0.6020    
## Week_36      -2375.88    1257.23  -1.890   0.0955 .  
## Week_37      -1847.96    2073.65  -0.891   0.3989    
## Week_38        649.91    1221.20   0.532   0.6091    
## Week_39         88.93    1025.59   0.087   0.9330    
## Week_40      -1053.59    1659.17  -0.635   0.5432    
## Week_41        804.23    1533.38   0.524   0.6142    
## Week_42       1521.51    1276.78   1.192   0.2675    
## Week_43         42.96    1581.70   0.027   0.9790    
## Week_44      -1031.52    1185.32  -0.870   0.4095    
## Week_45      -2714.56    1890.35  -1.436   0.1889    
## Week_46       3581.81    1774.99   2.018   0.0783 .  
## Week_47        268.70     803.14   0.335   0.7466    
## Week_48       1108.38    1039.64   1.066   0.3175    
## Week_49        443.45     996.90   0.445   0.6682    
## Week_50       -952.43    1045.11  -0.911   0.3888    
## Week_51       -326.53     762.11  -0.428   0.6796    
## Week_52        324.71    1325.00   0.245   0.8126    
## Week_53        -68.02     839.08  -0.081   0.9374    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7060 on 8 degrees of freedom
## Multiple R-squared:  0.9275, Adjusted R-squared:  0.4472 
## F-statistic: 1.931 on 53 and 8 DF,  p-value: 0.1623

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3765.4  -913.4  -359.8   954.4  4594.0 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 36184.14    6340.82   5.707 0.000451 ***
## Week_1        421.32     453.57   0.929 0.380112    
## Week_2       -406.31     313.42  -1.296 0.230984    
## Week_3        549.88     410.86   1.338 0.217566    
## Week_4         89.98     716.92   0.126 0.903221    
## Week_5        -56.65     408.42  -0.139 0.893107    
## Week_6      -1020.79     582.65  -1.752 0.117878    
## Week_7       -230.95     759.65  -0.304 0.768870    
## Week_8       1753.05     589.30   2.975 0.017740 *  
## Week_9       -853.03     545.28  -1.564 0.156359    
## Week_10       127.30     558.64   0.228 0.825462    
## Week_11     -1291.86     796.63  -1.622 0.143535    
## Week_12      -263.73     509.91  -0.517 0.618997    
## Week_13       251.56     584.25   0.431 0.678142    
## Week_14      1259.70    1219.28   1.033 0.331753    
## Week_15       477.74     874.29   0.546 0.599675    
## Week_16       -45.16     378.49  -0.119 0.907962    
## Week_17      -935.08     551.60  -1.695 0.128482    
## Week_18       539.98     422.68   1.278 0.237243    
## Week_19       531.49     264.58   2.009 0.079419 .  
## Week_20       759.79     589.74   1.288 0.233632    
## Week_21       -44.56     516.79  -0.086 0.933410    
## Week_22       -95.45     324.81  -0.294 0.776346    
## Week_23      -660.23     503.92  -1.310 0.226494    
## Week_24        94.10     510.52   0.184 0.858345    
## Week_25      -237.42     635.08  -0.374 0.718232    
## Week_26      -186.85     175.29  -1.066 0.317553    
## Week_27      1762.13     511.54   3.445 0.008762 ** 
## Week_28      -681.49     507.66  -1.342 0.216306    
## Week_29      -174.30     440.32  -0.396 0.702555    
## Week_30       302.91     328.84   0.921 0.383902    
## Week_31       918.94    1445.90   0.636 0.542818    
## Week_32       -66.10     428.41  -0.154 0.881195    
## Week_33      -718.92     667.20  -1.078 0.312663    
## Week_34      2947.85    1150.99   2.561 0.033587 *  
## Week_35     -1253.79     696.62  -1.800 0.109583    
## Week_36      1010.79     760.80   1.329 0.220628    
## Week_37      -676.69    1254.84  -0.539 0.604384    
## Week_38        86.66     738.99   0.117 0.909536    
## Week_39       125.72     620.62   0.203 0.844523    
## Week_40     -1368.57    1004.02  -1.363 0.209980    
## Week_41       722.08     927.90   0.778 0.458852    
## Week_42      1921.01     772.63   2.486 0.037737 *  
## Week_43      -572.65     957.14  -0.598 0.566194    
## Week_44      -751.93     717.28  -1.048 0.325130    
## Week_45      -841.69    1143.92  -0.736 0.482867    
## Week_46      1151.20    1074.11   1.072 0.315088    
## Week_47      -462.00     486.01  -0.951 0.369636    
## Week_48       592.93     629.12   0.942 0.373537    
## Week_49       263.89     603.26   0.437 0.673364    
## Week_50      -398.73     632.43  -0.630 0.545969    
## Week_51      -874.17     461.18  -1.896 0.094619 .  
## Week_52       585.33     801.80   0.730 0.486204    
## Week_53      -435.37     507.76  -0.857 0.416150    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4272 on 8 degrees of freedom
## Multiple R-squared:  0.9421, Adjusted R-squared:  0.5586 
## F-statistic: 2.456 on 53 and 8 DF,  p-value: 0.08845

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3404.7 -1029.7  -210.9   722.1  4629.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 23961.701   6607.473   3.626  0.00672 **
## Week_1       -702.709    472.641  -1.487  0.17539   
## Week_2        157.816    326.599   0.483  0.64189   
## Week_3       -292.068    428.139  -0.682  0.51439   
## Week_4       1208.512    747.071   1.618  0.14440   
## Week_5      -1049.263    425.592  -2.465  0.03899 * 
## Week_6       -630.246    607.154  -1.038  0.32961   
## Week_7        751.474    791.593   0.949  0.37025   
## Week_8       1135.322    614.080   1.849  0.10166   
## Week_9       -500.700    568.214  -0.881  0.40392   
## Week_10      -701.512    582.137  -1.205  0.26261   
## Week_11     -1225.466    830.130  -1.476  0.17812   
## Week_12      -449.506    531.350  -0.846  0.42215   
## Week_13       933.924    608.820   1.534  0.16358   
## Week_14      -633.648   1270.552  -0.499  0.63140   
## Week_15      1312.632    911.059   1.441  0.18762   
## Week_16       652.696    394.407   1.655  0.13654   
## Week_17      -634.967    574.801  -1.105  0.30142   
## Week_18      -487.901    440.455  -1.108  0.30017   
## Week_19       232.146    275.702   0.842  0.42423   
## Week_20      1266.244    614.536   2.060  0.07330 . 
## Week_21      -303.061    538.526  -0.563  0.58902   
## Week_22     -1094.305    338.472  -3.233  0.01200 * 
## Week_23       661.858    525.109   1.260  0.24304   
## Week_24        57.603    531.987   0.108  0.91644   
## Week_25        -4.102    661.788  -0.006  0.99521   
## Week_26       -61.315    182.661  -0.336  0.74575   
## Week_27       463.250    533.055   0.869  0.41014   
## Week_28       772.263    529.007   1.460  0.18246   
## Week_29      -846.214    458.834  -1.844  0.10237   
## Week_30       -29.721    342.664  -0.087  0.93301   
## Week_31      1311.893   1506.701   0.871  0.40928   
## Week_32       -88.776    446.424  -0.199  0.84733   
## Week_33     -1191.185    695.254  -1.713  0.12501   
## Week_34      1181.500   1199.389   0.985  0.35343   
## Week_35       366.011    725.915   0.504  0.62771   
## Week_36      -315.120    792.791  -0.397  0.70141   
## Week_37       915.710   1307.612   0.700  0.50360   
## Week_38     -1073.071    770.070  -1.393  0.20097   
## Week_39      -931.650    646.721  -1.441  0.18767   
## Week_40       377.127   1046.245   0.360  0.72784   
## Week_41      -810.362    966.925  -0.838  0.42631   
## Week_42       528.123    805.117   0.656  0.53026   
## Week_43     -1214.846    997.397  -1.218  0.25792   
## Week_44      1381.988    747.445   1.849  0.10164   
## Week_45     -1594.716   1192.025  -1.338  0.21774   
## Week_46      1576.992   1119.280   1.409  0.19652   
## Week_47       438.031    506.444   0.865  0.41227   
## Week_48      -479.170    655.580  -0.731  0.48569   
## Week_49        99.753    628.629   0.159  0.87785   
## Week_50      -512.787    659.030  -0.778  0.45891   
## Week_51         9.542    480.571   0.020  0.98464   
## Week_52      -301.734    835.522  -0.361  0.72735   
## Week_53      -197.042    529.111  -0.372  0.71927   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4452 on 8 degrees of freedom
## Multiple R-squared:  0.9341, Adjusted R-squared:  0.4972 
## F-statistic: 2.138 on 53 and 8 DF,  p-value: 0.1266

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -10582.2  -2734.3   -964.6   2582.2  12444.3 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept)  86931.8    19493.7   4.459  0.00211 **
## Week_1         622.7     1394.4   0.447  0.66705   
## Week_2        -813.6      963.6  -0.844  0.42301   
## Week_3       -1019.3     1263.1  -0.807  0.44301   
## Week_4        1161.6     2204.0   0.527  0.61246   
## Week_5         974.9     1255.6   0.776  0.45985   
## Week_6       -3132.8     1791.3  -1.749  0.11842   
## Week_7        2375.3     2335.4   1.017  0.33888   
## Week_8        1280.3     1811.7   0.707  0.49982   
## Week_9       -1105.3     1676.4  -0.659  0.52820   
## Week_10       -830.9     1717.5  -0.484  0.64148   
## Week_11       -555.4     2449.1  -0.227  0.82630   
## Week_12       -127.8     1567.6  -0.082  0.93701   
## Week_13       -593.5     1796.2  -0.330  0.74957   
## Week_14        511.5     3748.5   0.136  0.89483   
## Week_15       3093.1     2687.9   1.151  0.28306   
## Week_16       1995.0     1163.6   1.715  0.12477   
## Week_17      -2041.0     1695.8  -1.204  0.26317   
## Week_18        845.6     1299.5   0.651  0.53344   
## Week_19       1770.3      813.4   2.176  0.06120 . 
## Week_20       1772.9     1813.0   0.978  0.35679   
## Week_21        948.4     1588.8   0.597  0.56708   
## Week_22       -988.1      998.6  -0.989  0.35141   
## Week_23      -3053.1     1549.2  -1.971  0.08425 . 
## Week_24       1165.0     1569.5   0.742  0.47915   
## Week_25      -1809.0     1952.4  -0.927  0.38128   
## Week_26       -495.9      538.9  -0.920  0.38437   
## Week_27       3532.2     1572.6   2.246  0.05490 . 
## Week_28        912.1     1560.7   0.584  0.57503   
## Week_29       2202.8     1353.7   1.627  0.14232   
## Week_30        447.8     1010.9   0.443  0.66954   
## Week_31      -4140.4     4445.2  -0.931  0.37888   
## Week_32        103.0     1317.1   0.078  0.93961   
## Week_33      -4513.0     2051.2  -2.200  0.05898 . 
## Week_34       4737.9     3538.5   1.339  0.21738   
## Week_35      -1711.8     2141.6  -0.799  0.44720   
## Week_36       4970.6     2338.9   2.125  0.06629 . 
## Week_37      -1614.6     3857.8  -0.419  0.68658   
## Week_38        178.6     2271.9   0.079  0.93928   
## Week_39      -1377.1     1908.0  -0.722  0.49099   
## Week_40      -2170.8     3086.7  -0.703  0.50183   
## Week_41        841.9     2852.7   0.295  0.77541   
## Week_42       4085.1     2375.3   1.720  0.12377   
## Week_43      -2221.6     2942.6  -0.755  0.47189   
## Week_44        150.5     2205.2   0.068  0.94728   
## Week_45      -3618.9     3516.8  -1.029  0.33357   
## Week_46       4366.6     3302.2   1.322  0.22261   
## Week_47      -1076.3     1494.1  -0.720  0.49184   
## Week_48       3038.5     1934.1   1.571  0.15482   
## Week_49        538.8     1854.6   0.291  0.77881   
## Week_50      -2114.1     1944.3  -1.087  0.30856   
## Week_51      -1203.2     1417.8  -0.849  0.42073   
## Week_52       1993.5     2465.0   0.809  0.44207   
## Week_53      -3387.0     1561.0  -2.170  0.06184 . 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 13130 on 8 degrees of freedom
## Multiple R-squared:  0.9163, Adjusted R-squared:  0.3619 
## F-statistic: 1.653 on 53 and 8 DF,  p-value: 0.2305

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -7425.1 -1830.7   159.5  1640.6 10838.8 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept) 38575.24   13283.48   2.904   0.0198 *
## Week_1      -1403.29     950.18  -1.477   0.1780  
## Week_2        -75.63     656.59  -0.115   0.9111  
## Week_3      -1129.77     860.72  -1.313   0.2257  
## Week_4       2132.49    1501.89   1.420   0.1934  
## Week_5       -116.15     855.60  -0.136   0.8954  
## Week_6      -1094.49    1220.61  -0.897   0.3961  
## Week_7       2670.75    1591.40   1.678   0.1318  
## Week_8      -1066.28    1234.53  -0.864   0.4129  
## Week_9       1750.92    1142.32   1.533   0.1639  
## Week_10     -2646.91    1170.31  -2.262   0.0536 .
## Week_11      2260.02    1668.87   1.354   0.2127  
## Week_12     -2260.07    1068.21  -2.116   0.0673 .
## Week_13      1660.71    1223.96   1.357   0.2119  
## Week_14     -3561.38    2554.28  -1.394   0.2007  
## Week_15      2932.58    1831.57   1.601   0.1480  
## Week_16       -81.53     792.91  -0.103   0.9206  
## Week_17      1751.79    1155.56   1.516   0.1680  
## Week_18      -435.27     885.48  -0.492   0.6362  
## Week_19       358.92     554.26   0.648   0.5354  
## Week_20       957.48    1235.45   0.775   0.4606  
## Week_21       479.84    1082.64   0.443   0.6693  
## Week_22       191.51     680.45   0.281   0.7855  
## Week_23       270.30    1055.66   0.256   0.8044  
## Week_24       957.57    1069.49   0.895   0.3967  
## Week_25      -827.69    1330.44  -0.622   0.5512  
## Week_26        87.36     367.22   0.238   0.8179  
## Week_27     -1019.80    1071.64  -0.952   0.3692  
## Week_28      1946.71    1063.50   1.830   0.1046  
## Week_29      -162.84     922.43  -0.177   0.8643  
## Week_30       244.00     688.88   0.354   0.7323  
## Week_31     -5340.99    3029.03  -1.763   0.1159  
## Week_32     -1520.77     897.48  -1.694   0.1286  
## Week_33     -1147.44    1397.72  -0.821   0.4355  
## Week_34      3479.24    2411.22   1.443   0.1870  
## Week_35     -3175.18    1459.36  -2.176   0.0613 .
## Week_36      3175.92    1593.80   1.993   0.0814 .
## Week_37      2750.35    2628.79   1.046   0.3260  
## Week_38     -2153.98    1548.13  -1.391   0.2016  
## Week_39      -373.91    1300.15  -0.288   0.7810  
## Week_40      1410.62    2103.34   0.671   0.5213  
## Week_41     -1818.99    1943.88  -0.936   0.3768  
## Week_42     -1358.87    1618.59  -0.840   0.4255  
## Week_43       339.94    2005.14   0.170   0.8696  
## Week_44      2361.83    1502.64   1.572   0.1546  
## Week_45      -844.36    2396.41  -0.352   0.7337  
## Week_46      1400.81    2250.17   0.623   0.5509  
## Week_47      -434.00    1018.14  -0.426   0.6812  
## Week_48      -826.90    1317.96  -0.627   0.5479  
## Week_49       179.49    1263.78   0.142   0.8906  
## Week_50      -818.68    1324.90  -0.618   0.5538  
## Week_51       523.05     966.13   0.541   0.6030  
## Week_52     -1834.04    1679.71  -1.092   0.3067  
## Week_53      -330.80    1063.71  -0.311   0.7638  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8950 on 8 degrees of freedom
## Multiple R-squared:  0.885,  Adjusted R-squared:  0.1231 
## F-statistic: 1.162 on 53 and 8 DF,  p-value: 0.4452

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -9574.4 -2626.2  -828.6  2319.2 12062.2 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 96214.07   18287.79   5.261 0.000763 ***
## Week_1        864.57    1308.15   0.661 0.527240    
## Week_2       -647.67     903.94  -0.716 0.494067    
## Week_3       1316.81    1184.98   1.111 0.298740    
## Week_4       -216.05    2067.70  -0.104 0.919354    
## Week_5        -50.65    1177.93  -0.043 0.966754    
## Week_6      -2597.43    1680.45  -1.546 0.160764    
## Week_7       1128.01    2190.93   0.515 0.620575    
## Week_8       1744.02    1699.62   1.026 0.334855    
## Week_9      -1174.94    1572.67  -0.747 0.476387    
## Week_10        19.93    1611.20   0.012 0.990432    
## Week_11     -3106.88    2297.59  -1.352 0.213281    
## Week_12      -749.85    1470.64  -0.510 0.623899    
## Week_13       966.28    1685.06   0.573 0.582104    
## Week_14      1617.57    3516.56   0.460 0.657769    
## Week_15      2003.33    2521.58   0.794 0.449843    
## Week_16      1978.71    1091.62   1.813 0.107456    
## Week_17     -2610.72    1590.90  -1.641 0.139419    
## Week_18      1201.27    1219.06   0.985 0.353288    
## Week_19      2049.35     763.07   2.686 0.027682 *  
## Week_20      1696.67    1700.88   0.998 0.347722    
## Week_21      -414.95    1490.50  -0.278 0.787770    
## Week_22      -642.76     936.80  -0.686 0.512030    
## Week_23     -2279.89    1453.37  -1.569 0.155357    
## Week_24       964.27    1472.40   0.655 0.530909    
## Week_25     -2834.51    1831.66  -1.548 0.160329    
## Week_26      -253.21     505.56  -0.501 0.629964    
## Week_27      4813.40    1475.36   3.263 0.011484 *  
## Week_28       465.76    1464.15   0.318 0.758547    
## Week_29       947.86    1269.94   0.746 0.476794    
## Week_30       276.49     948.41   0.292 0.778061    
## Week_31      4293.72    4170.16   1.030 0.333305    
## Week_32       -20.41    1235.59  -0.017 0.987228    
## Week_33     -3697.88    1924.28  -1.922 0.090878 .  
## Week_34      7274.26    3319.60   2.191 0.059799 .  
## Week_35      -690.19    2009.15  -0.344 0.740057    
## Week_36      2965.91    2194.24   1.352 0.213451    
## Week_37     -5179.06    3619.13  -1.431 0.190304    
## Week_38       186.13    2131.36   0.087 0.932556    
## Week_39     -1639.98    1789.96  -0.916 0.386342    
## Week_40     -2550.36    2895.74  -0.881 0.404146    
## Week_41      2136.35    2676.20   0.798 0.447757    
## Week_42      5077.45    2228.36   2.279 0.052188 .  
## Week_43     -2317.80    2760.54  -0.840 0.425501    
## Week_44      -549.43    2068.73  -0.266 0.797272    
## Week_45     -7212.95    3299.22  -2.186 0.060271 .  
## Week_46      7210.22    3097.88   2.327 0.048352 *  
## Week_47       -70.61    1401.71  -0.050 0.961059    
## Week_48      3032.03    1814.48   1.671 0.133262    
## Week_49      1772.54    1739.88   1.019 0.338130    
## Week_50     -3077.15    1824.03  -1.687 0.130084    
## Week_51     -1938.64    1330.10  -1.458 0.183080    
## Week_52      2267.84    2312.51   0.981 0.355471    
## Week_53     -2077.35    1464.44  -1.419 0.193798    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 12320 on 8 degrees of freedom
## Multiple R-squared:  0.9484, Adjusted R-squared:  0.6068 
## F-statistic: 2.776 on 53 and 8 DF,  p-value: 0.06325

Kelowna weekly

## [1] "NA value found at row 17 and column 47"
## [1] "NA value found at row 17 and column 48"
## [1] "NA value found at row 17 and column 49"
## [1] "NA value found at row 57 and column 55"
## [1] "There are 4  NA in the matrix X in Kelowna station"
## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -30154.8  -6135.8    712.3   7224.2  26419.6 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 254454.9    70907.1   3.589  0.01152 * 
## Week_1        9439.3     3995.8   2.362  0.05611 . 
## Week_2       -3840.2     2552.3  -1.505  0.18313   
## Week_3       -4066.3     4223.3  -0.963  0.37281   
## Week_4        6566.7     3577.6   1.836  0.11610   
## Week_5       -6977.7     3332.6  -2.094  0.08117 . 
## Week_6        2346.9     2280.3   1.029  0.34306   
## Week_7       -4405.8     2991.0  -1.473  0.19118   
## Week_8        6088.8     3069.5   1.984  0.09455 . 
## Week_9       -2005.2     4852.3  -0.413  0.69379   
## Week_10       -197.9     3949.4  -0.050  0.96166   
## Week_11      -5271.4     3296.5  -1.599  0.16092   
## Week_12       -314.6     3867.2  -0.081  0.93780   
## Week_13       2065.0     5988.0   0.345  0.74197   
## Week_14       6474.1     5175.1   1.251  0.25749   
## Week_15      15634.6     4786.3   3.267  0.01711 * 
## Week_16      -1074.1     4244.7  -0.253  0.80867   
## Week_17     -24290.2     4655.2  -5.218  0.00198 **
## Week_18       2128.1     3328.9   0.639  0.54626   
## Week_19       5076.9     3173.8   1.600  0.16080   
## Week_20       1830.8     2936.3   0.624  0.55590   
## Week_21       5182.3     3423.1   1.514  0.18082   
## Week_22     -12541.4     3919.7  -3.200  0.01861 * 
## Week_23      -1653.5     3275.6  -0.505  0.63171   
## Week_24       9563.5     3834.2   2.494  0.04689 * 
## Week_25      -8258.8     3408.0  -2.423  0.05162 . 
## Week_26       2224.8     1214.6   1.832  0.11670   
## Week_27       1278.9     5758.2   0.222  0.83160   
## Week_28       5099.3     6685.0   0.763  0.47449   
## Week_29       -308.1     8341.8  -0.037  0.97174   
## Week_30      -1188.9     6547.5  -0.182  0.86189   
## Week_31       1457.7     5650.9   0.258  0.80506   
## Week_32      -2317.8     9721.5  -0.238  0.81949   
## Week_33      17332.7     7236.2   2.395  0.05364 . 
## Week_34       6067.5    11218.0   0.541  0.60807   
## Week_35       7128.2     6922.9   1.030  0.34288   
## Week_36     -34922.4     6136.6  -5.691  0.00127 **
## Week_37       9970.6     5411.6   1.842  0.11499   
## Week_38       1583.9     5484.0   0.289  0.78244   
## Week_39       1229.5     5659.8   0.217  0.83523   
## Week_40       3828.9     6468.2   0.592  0.57549   
## Week_41     -13650.5     6388.0  -2.137  0.07648 . 
## Week_42       3479.1     7900.1   0.440  0.67508   
## Week_43       5254.8     8613.5   0.610  0.56419   
## Week_44       2164.5     3729.6   0.580  0.58279   
## Week_45       2399.5     6028.6   0.398  0.70439   
## Week_46      -4232.3     4628.8  -0.914  0.39580   
## Week_47       5739.4     4220.4   1.360  0.22273   
## Week_48       2652.9     3446.3   0.770  0.47065   
## Week_49      -5711.5     3232.3  -1.767  0.12765   
## Week_50       2010.6     5630.5   0.357  0.73325   
## Week_51       4146.0     3824.5   1.084  0.31996   
## Week_52       1642.3     3186.3   0.515  0.62468   
## Week_53      -1057.9     2569.2  -0.412  0.69481   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 35570 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9606, Adjusted R-squared:  0.6121 
## F-statistic: 2.757 on 53 and 6 DF,  p-value: 0.1008

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##  -4248  -1103     18   1152   3842 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 33590.31   10323.46   3.254  0.01738 * 
## Week_1       1054.09     581.76   1.812  0.11996   
## Week_2       -664.55     371.59  -1.788  0.12393   
## Week_3       -277.34     614.87  -0.451  0.66779   
## Week_4        586.74     520.87   1.126  0.30300   
## Week_5       -715.63     485.20  -1.475  0.19068   
## Week_6        369.49     331.98   1.113  0.30831   
## Week_7       -702.58     435.47  -1.613  0.15779   
## Week_8        913.15     446.89   2.043  0.08704 . 
## Week_9       -553.82     706.46  -0.784  0.46289   
## Week_10       198.69     575.00   0.346  0.74148   
## Week_11      -675.12     479.94  -1.407  0.20915   
## Week_12       594.93     563.03   1.057  0.33134   
## Week_13      -550.34     871.79  -0.631  0.55114   
## Week_14      1322.64     753.44   1.755  0.12971   
## Week_15      1404.07     696.85   2.015  0.09054 . 
## Week_16       -50.45     617.99  -0.082  0.93759   
## Week_17     -2469.89     677.76  -3.644  0.01078 * 
## Week_18       138.19     484.65   0.285  0.78513   
## Week_19       588.05     462.08   1.273  0.25024   
## Week_20       143.15     427.50   0.335  0.74913   
## Week_21       553.64     498.37   1.111  0.30914   
## Week_22     -1078.15     570.67  -1.889  0.10776   
## Week_23        94.57     476.90   0.198  0.84936   
## Week_24       422.13     558.22   0.756  0.47816   
## Week_25      -389.16     496.17  -0.784  0.46268   
## Week_26       160.19     176.83   0.906  0.39991   
## Week_27       140.03     838.34   0.167  0.87283   
## Week_28      -198.91     973.28  -0.204  0.84482   
## Week_29       408.55    1214.49   0.336  0.74802   
## Week_30      -318.03     953.26  -0.334  0.75001   
## Week_31      -392.14     822.73  -0.477  0.65049   
## Week_32       724.27    1415.37   0.512  0.62713   
## Week_33      1425.23    1053.53   1.353  0.22487   
## Week_34       768.77    1633.24   0.471  0.65448   
## Week_35       474.34    1007.91   0.471  0.65453   
## Week_36     -3318.04     893.44  -3.714  0.00992 **
## Week_37       940.77     787.88   1.194  0.27752   
## Week_38       593.36     798.42   0.743  0.48546   
## Week_39       798.80     824.02   0.969  0.36979   
## Week_40       762.89     941.72   0.810  0.44881   
## Week_41     -1889.89     930.04  -2.032  0.08841 . 
## Week_42       -65.53    1150.18  -0.057  0.95641   
## Week_43        47.78    1254.05   0.038  0.97084   
## Week_44       461.84     543.00   0.851  0.42766   
## Week_45      -261.94     877.71  -0.298  0.77543   
## Week_46      -375.77     673.92  -0.558  0.59730   
## Week_47       219.60     614.45   0.357  0.73304   
## Week_48       -28.28     501.76  -0.056  0.95689   
## Week_49      -530.60     470.60  -1.128  0.30259   
## Week_50       464.74     819.75   0.567  0.59133   
## Week_51       348.08     556.81   0.625  0.55490   
## Week_52       324.56     463.90   0.700  0.51036   
## Week_53      -280.66     374.06  -0.750  0.48145   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5178 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9289, Adjusted R-squared:  0.3007 
## F-statistic: 1.479 on 53 and 6 DF,  p-value: 0.3307

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -14723.5  -3382.8    229.2   4196.2  13326.0 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) 105692.57   31850.27   3.318   0.0160 *
## Week_1        2125.89    1794.85   1.184   0.2810  
## Week_2       -1713.57    1146.45  -1.495   0.1856  
## Week_3         527.42    1897.01   0.278   0.7903  
## Week_4         885.51    1607.00   0.551   0.6015  
## Week_5       -1191.23    1496.94  -0.796   0.4565  
## Week_6         388.69    1024.25   0.379   0.7174  
## Week_7        -858.96    1343.53  -0.639   0.5462  
## Week_8        1620.62    1378.77   1.175   0.2844  
## Week_9       -1896.36    2179.59  -0.870   0.4177  
## Week_10       1186.41    1774.00   0.669   0.5285  
## Week_11      -1862.62    1480.74  -1.258   0.2552  
## Week_12       1480.00    1737.07   0.852   0.4269  
## Week_13      -2149.96    2689.69  -0.799   0.4546  
## Week_14       3958.42    2324.55   1.703   0.1395  
## Week_15       1740.71    2149.94   0.810   0.4490  
## Week_16       1125.31    1906.64   0.590   0.5766  
## Week_17      -4571.97    2091.04  -2.186   0.0714 .
## Week_18       -526.76    1495.27  -0.352   0.7367  
## Week_19       1760.62    1425.62   1.235   0.2630  
## Week_20        814.17    1318.93   0.617   0.5597  
## Week_21       1208.20    1537.60   0.786   0.4619  
## Week_22      -3277.87    1760.65  -1.862   0.1120  
## Week_23        387.68    1471.34   0.263   0.8010  
## Week_24       1790.94    1722.25   1.040   0.3385  
## Week_25      -2411.54    1530.79  -1.575   0.1662  
## Week_26       1273.79     545.56   2.335   0.0583 .
## Week_27       -817.11    2586.47  -0.316   0.7628  
## Week_28         58.59    3002.79   0.020   0.9851  
## Week_29       2220.45    3746.98   0.593   0.5751  
## Week_30      -1671.65    2941.03  -0.568   0.5904  
## Week_31        658.52    2538.31   0.259   0.8040  
## Week_32       1744.70    4366.73   0.400   0.7033  
## Week_33       2876.75    3250.40   0.885   0.4102  
## Week_34       4771.24    5038.91   0.947   0.3803  
## Week_35       1581.16    3109.63   0.508   0.6293  
## Week_36      -7086.68    2756.46  -2.571   0.0423 *
## Week_37       1988.60    2430.80   0.818   0.4446  
## Week_38       -107.79    2463.32  -0.044   0.9665  
## Week_39        981.25    2542.31   0.386   0.7128  
## Week_40        853.83    2905.41   0.294   0.7788  
## Week_41      -3789.38    2869.38  -1.321   0.2348  
## Week_42        331.13    3548.57   0.093   0.9287  
## Week_43       -598.94    3869.04  -0.155   0.8821  
## Week_44       1464.76    1675.28   0.874   0.4156  
## Week_45      -1264.21    2707.93  -0.467   0.6571  
## Week_46       -960.49    2079.20  -0.462   0.6604  
## Week_47       -120.36    1895.73  -0.063   0.9514  
## Week_48         82.81    1548.04   0.053   0.9591  
## Week_49       -633.68    1451.90  -0.436   0.6778  
## Week_50       2907.58    2529.13   1.150   0.2940  
## Week_51       -510.12    1717.89  -0.297   0.7765  
## Week_52       1543.22    1431.23   1.078   0.3224  
## Week_53       -770.75    1154.06  -0.668   0.5291  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15980 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9185, Adjusted R-squared:  0.1982 
## F-statistic: 1.275 on 53 and 6 DF,  p-value: 0.4139

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##  -6787  -2096    146   1982  12627 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 120001.02   20945.20   5.729  0.00123 **
## Week_1        1001.52    1180.32   0.849  0.42870   
## Week_2          85.80     753.92   0.114  0.91310   
## Week_3       -1457.72    1247.50  -1.169  0.28692   
## Week_4        1821.07    1056.79   1.723  0.13562   
## Week_5       -1664.96     984.41  -1.691  0.14173   
## Week_6          84.04     673.56   0.125  0.90479   
## Week_7        -421.76     883.52  -0.477  0.65000   
## Week_8         973.76     906.70   1.074  0.32412   
## Week_9        -161.96    1433.33  -0.113  0.91372   
## Week_10       -288.02    1166.61  -0.247  0.81323   
## Week_11       -638.92     973.76  -0.656  0.53607   
## Week_12          8.31    1142.32   0.007  0.99443   
## Week_13        527.75    1768.78   0.298  0.77548   
## Week_14        530.75    1528.66   0.347  0.74029   
## Week_15       2076.98    1413.83   1.469  0.19221   
## Week_16       -548.24    1253.83  -0.437  0.67723   
## Week_17      -3229.28    1375.10  -2.348  0.05718 . 
## Week_18        441.39     983.31   0.449  0.66928   
## Week_19       -197.83     937.51  -0.211  0.83986   
## Week_20        307.69     867.35   0.355  0.73491   
## Week_21        888.25    1011.15   0.878  0.41348   
## Week_22      -1571.37    1157.83  -1.357  0.22356   
## Week_23       -713.96     967.58  -0.738  0.48843   
## Week_24        466.58    1132.57   0.412  0.69468   
## Week_25        494.08    1006.67   0.491  0.64099   
## Week_26       -399.71     358.77  -1.114  0.30786   
## Week_27       1399.70    1700.90   0.823  0.44202   
## Week_28        536.30    1974.68   0.272  0.79504   
## Week_29        717.21    2464.07   0.291  0.78080   
## Week_30        448.10    1934.06   0.232  0.82448   
## Week_31      -1275.62    1669.23  -0.764  0.47372   
## Week_32       2028.87    2871.63   0.707  0.50636   
## Week_33       1298.57    2137.51   0.608  0.56578   
## Week_34      -2967.45    3313.66  -0.896  0.40500   
## Week_35       2001.87    2044.94   0.979  0.36542   
## Week_36      -5875.36    1812.69  -3.241  0.01766 * 
## Week_37       2532.70    1598.53   1.584  0.16420   
## Week_38       -139.24    1619.92  -0.086  0.93430   
## Week_39        903.11    1671.86   0.540  0.60852   
## Week_40        822.39    1910.64   0.430  0.68192   
## Week_41       -892.41    1886.95  -0.473  0.65297   
## Week_42        675.40    2333.59   0.289  0.78200   
## Week_43       2540.30    2544.34   0.998  0.35663   
## Week_44       -522.64    1101.69  -0.474  0.65198   
## Week_45        366.61    1780.77   0.206  0.84370   
## Week_46        681.99    1367.31   0.499  0.63569   
## Week_47        527.08    1246.66   0.423  0.68718   
## Week_48       1045.80    1018.01   1.027  0.34390   
## Week_49      -1266.77     954.79  -1.327  0.23285   
## Week_50        241.37    1663.19   0.145  0.88937   
## Week_51        830.84    1129.71   0.735  0.48981   
## Week_52       -582.00     941.20  -0.618  0.55906   
## Week_53        473.67     758.93   0.624  0.55551   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10510 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.8785, Adjusted R-squared:  -0.1946 
## F-statistic: 0.8187 on 53 and 6 DF,  p-value: 0.6899

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4257.5  -909.1    62.1  1143.0  4236.3 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) 29967.882  10530.540   2.846   0.0293 *
## Week_1        810.150    593.426   1.365   0.2212  
## Week_2       -652.709    379.046  -1.722   0.1359  
## Week_3        131.664    627.203   0.210   0.8407  
## Week_4        193.406    531.316   0.364   0.7283  
## Week_5       -450.415    494.929  -0.910   0.3979  
## Week_6        256.779    338.644   0.758   0.4770  
## Week_7       -664.789    444.206  -1.497   0.1851  
## Week_8        830.048    455.858   1.821   0.1185  
## Week_9       -403.779    720.629  -0.560   0.5956  
## Week_10       159.243    586.531   0.271   0.7951  
## Week_11      -714.886    489.572  -1.460   0.1945  
## Week_12       505.785    574.321   0.881   0.4124  
## Week_13      -373.711    889.282  -0.420   0.6889  
## Week_14      1195.488    768.557   1.555   0.1708  
## Week_15       390.651    710.826   0.550   0.6025  
## Week_16       696.135    630.385   1.104   0.3118  
## Week_17     -2186.647    691.354  -3.163   0.0195 *
## Week_18       138.100    494.376   0.279   0.7894  
## Week_19       704.842    471.349   1.495   0.1854  
## Week_20       169.868    436.073   0.390   0.7103  
## Week_21       525.853    508.371   1.034   0.3408  
## Week_22      -838.146    582.118  -1.440   0.2000  
## Week_23      -210.753    486.465  -0.433   0.6800  
## Week_24       533.804    569.420   0.937   0.3847  
## Week_25      -462.799    506.121  -0.914   0.3958  
## Week_26       288.195    180.377   1.598   0.1612  
## Week_27      -413.028    855.157  -0.483   0.6462  
## Week_28       129.790    992.801   0.131   0.9003  
## Week_29        55.489   1238.850   0.045   0.9657  
## Week_30      -425.918    972.382  -0.438   0.6767  
## Week_31        86.052    839.231   0.103   0.9217  
## Week_32      1269.551   1443.757   0.879   0.4130  
## Week_33       773.410   1074.667   0.720   0.4988  
## Week_34      1592.584   1665.997   0.956   0.3760  
## Week_35        -2.384   1028.127  -0.002   0.9982  
## Week_36     -2857.637    911.358  -3.136   0.0202 *
## Week_37       684.519    803.686   0.852   0.4270  
## Week_38       563.159    814.440   0.691   0.5151  
## Week_39       480.921    840.554   0.572   0.5880  
## Week_40       469.918    960.605   0.489   0.6421  
## Week_41     -1648.595    948.694  -1.738   0.1329  
## Week_42      1095.947   1173.252   0.934   0.3863  
## Week_43      -744.176   1279.207  -0.582   0.5819  
## Week_44       450.345    553.891   0.813   0.4472  
## Week_45      -261.521    895.313  -0.292   0.7800  
## Week_46        30.213    687.438   0.044   0.9664  
## Week_47       164.912    626.777   0.263   0.8013  
## Week_48      -232.763    511.822  -0.455   0.6653  
## Week_49      -519.140    480.037  -1.081   0.3210  
## Week_50       525.198    836.196   0.628   0.5531  
## Week_51       333.531    567.981   0.587   0.5785  
## Week_52       197.264    473.202   0.417   0.6913  
## Week_53      -308.792    381.563  -0.809   0.4492  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5282 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9297, Adjusted R-squared:  0.3085 
## F-statistic: 1.497 on 53 and 6 DF,  p-value: 0.3244

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3528.5  -943.8   -85.9  1063.8  3455.6 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 60077.04    9333.07   6.437 0.000665 ***
## Week_1         15.02     525.94   0.029 0.978149    
## Week_2       -354.00     335.94  -1.054 0.332572    
## Week_3        717.52     555.88   1.291 0.244281    
## Week_4       -340.72     470.90  -0.724 0.496568    
## Week_5        217.01     438.65   0.495 0.638393    
## Week_6       -365.02     300.14  -1.216 0.269581    
## Week_7        165.25     393.69   0.420 0.689288    
## Week_8         29.36     404.02   0.073 0.944433    
## Week_9       -166.57     638.68  -0.261 0.802968    
## Week_10      -234.08     519.83  -0.450 0.668306    
## Week_11       169.53     433.90   0.391 0.709506    
## Week_12       262.84     509.01   0.516 0.624073    
## Week_13     -1076.35     788.16  -1.366 0.221027    
## Week_14      1078.02     681.16   1.583 0.164596    
## Week_15     -1559.96     630.00  -2.476 0.048056 *  
## Week_16      1827.43     558.70   3.271 0.017016 *  
## Week_17       386.71     612.74   0.631 0.551235    
## Week_18      -492.61     438.16  -1.124 0.303853    
## Week_19        11.51     417.75   0.028 0.978914    
## Week_20       989.29     386.49   2.560 0.042925 *  
## Week_21       -57.21     450.56  -0.127 0.903112    
## Week_22       436.35     515.92   0.846 0.430113    
## Week_23       317.56     431.15   0.737 0.489182    
## Week_24      -733.99     504.67  -1.454 0.196068    
## Week_25      -240.76     448.57  -0.537 0.610760    
## Week_26       209.51     159.87   1.311 0.237947    
## Week_27       -14.21     757.91  -0.019 0.985648    
## Week_28      -131.89     879.91  -0.150 0.885762    
## Week_29       206.71    1097.98   0.188 0.856876    
## Week_30      -974.75     861.81  -1.131 0.301207    
## Week_31      1077.29     743.80   1.448 0.197681    
## Week_32       947.29    1279.58   0.740 0.487056    
## Week_33     -1773.74     952.46  -1.862 0.111871    
## Week_34      3870.94    1476.55   2.622 0.039501 *  
## Week_35       675.84     911.21   0.742 0.486281    
## Week_36     -1057.40     807.72  -1.309 0.238394    
## Week_37       317.53     712.30   0.446 0.671388    
## Week_38       841.74     721.83   1.166 0.287815    
## Week_39     -1685.51     744.97  -2.263 0.064326 .  
## Week_40       103.02     851.37   0.121 0.907638    
## Week_41      1151.08     840.81   1.369 0.220034    
## Week_42      1809.87    1039.84   1.741 0.132413    
## Week_43      -637.56    1133.74  -0.562 0.594247    
## Week_44       724.07     490.91   1.475 0.190668    
## Week_45     -1348.15     793.50  -1.699 0.140237    
## Week_46       794.57     609.27   1.304 0.239978    
## Week_47      -391.25     555.50  -0.704 0.507634    
## Week_48      -284.07     453.62  -0.626 0.554229    
## Week_49       380.32     425.45   0.894 0.405789    
## Week_50       385.14     741.11   0.520 0.621892    
## Week_51       -95.59     503.39  -0.190 0.855654    
## Week_52        44.52     419.39   0.106 0.918929    
## Week_53      -356.12     338.17  -1.053 0.332864    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4681 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9412, Adjusted R-squared:  0.4215 
## F-statistic: 1.811 on 53 and 6 DF,  p-value: 0.2339

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -9439.1 -2055.9  -257.6  2199.7  7010.1 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 68156.459  21733.187   3.136  0.02017 * 
## Week_1       2188.683   1224.726   1.787  0.12415   
## Week_2      -1597.258    782.284  -2.042  0.08723 . 
## Week_3       -942.923   1294.437  -0.728  0.49378   
## Week_4       1141.234   1096.544   1.041  0.33810   
## Week_5       -377.968   1021.447  -0.370  0.72407   
## Week_6        848.260    698.902   1.214  0.27046   
## Week_7      -2028.193    916.763  -2.212  0.06892 . 
## Week_8       2191.678    940.812   2.330  0.05868 . 
## Week_9      -1646.316   1487.251  -1.107  0.31071   
## Week_10      -883.528   1210.498  -0.730  0.49296   
## Week_11       227.101   1010.390   0.225  0.82962   
## Week_12      1723.757   1185.298   1.454  0.19610   
## Week_13     -2866.898   1835.322  -1.562  0.16930   
## Week_14      2192.277   1586.166   1.382  0.21619   
## Week_15      2605.230   1467.021   1.776  0.12610   
## Week_16       236.891   1301.004   0.182  0.86151   
## Week_17     -5458.131   1426.834  -3.825  0.00871 **
## Week_18      2930.105   1020.306   2.872  0.02836 * 
## Week_19       379.006    972.781   0.390  0.71028   
## Week_20       667.900    899.978   0.742  0.48603   
## Week_21       319.439   1049.189   0.304  0.77106   
## Week_22      -706.750   1201.390  -0.588  0.57780   
## Week_23       576.682   1003.979   0.574  0.58657   
## Week_24      -234.974   1175.183  -0.200  0.84813   
## Week_25     -1749.385   1044.545  -1.675  0.14500   
## Week_26       691.304    372.267   1.857  0.11269   
## Week_27      -572.160   1764.893  -0.324  0.75680   
## Week_28       -84.217   2048.967  -0.041  0.96855   
## Week_29      1838.951   2556.769   0.719  0.49903   
## Week_30     -1449.662   2006.826  -0.722  0.49725   
## Week_31     -1477.208   1732.026  -0.853  0.42646   
## Week_32     -1827.702   2979.662  -0.613  0.56213   
## Week_33      3005.513   2217.924   1.355  0.22418   
## Week_34      5139.220   3438.326   1.495  0.18562   
## Week_35      1735.325   2121.874   0.818  0.44471   
## Week_36     -4388.823   1880.883  -2.333  0.05837 . 
## Week_37      2658.598   1658.667   1.603  0.16009   
## Week_38       311.665   1680.862   0.185  0.85901   
## Week_39      2190.043   1734.756   1.262  0.25363   
## Week_40     -1424.282   1982.521  -0.718  0.49951   
## Week_41     -3150.295   1957.938  -1.609  0.15874   
## Week_42      -997.026   2421.387  -0.412  0.69482   
## Week_43      -503.172   2640.060  -0.191  0.85513   
## Week_44       810.417   1143.133   0.709  0.50496   
## Week_45      -539.623   1847.769  -0.292  0.78009   
## Week_46     -1509.091   1418.752  -1.064  0.32840   
## Week_47      -667.043   1293.557  -0.516  0.62453   
## Week_48       913.235   1056.311   0.865  0.42050   
## Week_49         7.926    990.713   0.008  0.99388   
## Week_50       979.602   1725.762   0.568  0.59087   
## Week_51       -57.064   1172.212  -0.049  0.96275   
## Week_52      2582.939    976.605   2.645  0.03829 * 
## Week_53     -2250.581    787.479  -2.858  0.02888 * 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10900 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9517, Adjusted R-squared:  0.5249 
## F-statistic:  2.23 on 53 and 6 DF,  p-value: 0.1572

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5109.1 -1735.2   102.4  1843.0  6184.9 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)   
## (Intercept) 46765.75   15381.26   3.040  0.02279 * 
## Week_1        934.18     866.78   1.078  0.32255   
## Week_2       -124.30     553.65  -0.225  0.82981   
## Week_3       -828.83     916.11  -0.905  0.40048   
## Week_4        542.37     776.06   0.699  0.51079   
## Week_5       -959.23     722.91  -1.327  0.23280   
## Week_6       1208.17     494.63   2.443  0.05030 . 
## Week_7       -566.20     648.82  -0.873  0.41640   
## Week_8       -356.02     665.84  -0.535  0.61208   
## Week_9        746.36    1052.57   0.709  0.50488   
## Week_10      -184.80     856.71  -0.216  0.83636   
## Week_11      -186.98     715.08  -0.261  0.80247   
## Week_12       304.49     838.87   0.363  0.72907   
## Week_13     -1704.26    1298.91  -1.312  0.23746   
## Week_14       615.22    1122.58   0.548  0.60344   
## Week_15      3881.69    1038.26   3.739  0.00964 **
## Week_16     -2124.09     920.76  -2.307  0.06053 . 
## Week_17     -2163.89    1009.82  -2.143  0.07585 . 
## Week_18       644.20     722.10   0.892  0.40668   
## Week_19       572.37     688.47   0.831  0.43759   
## Week_20     -1126.34     636.94  -1.768  0.12741   
## Week_21       184.23     742.54   0.248  0.81233   
## Week_22      -301.90     850.26  -0.355  0.73469   
## Week_23      2346.29     710.55   3.302  0.01637 * 
## Week_24       296.40     831.71   0.356  0.73376   
## Week_25     -1459.61     739.26  -1.974  0.09576 . 
## Week_26       130.54     263.46   0.495  0.63790   
## Week_27       178.04    1249.07   0.143  0.89132   
## Week_28      1385.44    1450.12   0.955  0.37627   
## Week_29     -1226.06    1809.51  -0.678  0.52330   
## Week_30      1847.09    1420.29   1.301  0.24114   
## Week_31      -855.39    1225.81  -0.698  0.51141   
## Week_32     -4285.81    2108.80  -2.032  0.08838 . 
## Week_33      3378.40    1569.69   2.152  0.07487 . 
## Week_34      1709.14    2433.41   0.702  0.50877   
## Week_35     -2221.66    1501.72  -1.479  0.18952   
## Week_36     -1743.00    1331.16  -1.309  0.23831   
## Week_37       934.09    1173.89   0.796  0.45651   
## Week_38      1060.48    1189.60   0.891  0.40701   
## Week_39      1056.07    1227.74   0.860  0.42273   
## Week_40      -238.15    1403.09  -0.170  0.87080   
## Week_41       198.43    1385.69   0.143  0.89082   
## Week_42     -2870.61    1713.69  -1.675  0.14493   
## Week_43      4173.14    1868.45   2.233  0.06695 . 
## Week_44      -820.15     809.03  -1.014  0.34983   
## Week_45      -446.36    1307.72  -0.341  0.74449   
## Week_46      -848.81    1004.10  -0.845  0.43033   
## Week_47      1047.42     915.49   1.144  0.29616   
## Week_48      -243.87     747.58  -0.326  0.75534   
## Week_49        69.04     701.16   0.098  0.92477   
## Week_50     -1356.34    1221.38  -1.111  0.30929   
## Week_51       449.93     829.61   0.542  0.60712   
## Week_52      1045.16     691.17   1.512  0.18125   
## Week_53     -1220.27     557.32  -2.190  0.07112 . 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7715 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.9336, Adjusted R-squared:  0.3473 
## F-statistic: 1.592 on 53 and 6 DF,  p-value: 0.2929

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -10104.8  -2583.3   -389.8   3367.5   7371.2 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)   
## (Intercept)  96670.63   25554.74   3.783  0.00915 **
## Week_1        3451.33    1440.08   2.397  0.05354 . 
## Week_2       -1520.17     919.84  -1.653  0.14949   
## Week_3       -1670.56    1522.05  -1.098  0.31447   
## Week_4        2831.99    1289.36   2.196  0.07045 . 
## Week_5       -2441.82    1201.06  -2.033  0.08829 . 
## Week_6          70.14     821.80   0.085  0.93476   
## Week_7        -398.52    1077.97  -0.370  0.72430   
## Week_8        1010.82    1106.24   0.914  0.39609   
## Week_9        -764.43    1748.77  -0.437  0.67731   
## Week_10       -188.55    1423.35  -0.132  0.89894   
## Week_11      -1134.97    1188.06  -0.955  0.37631   
## Week_12       1074.31    1393.72   0.771  0.47007   
## Week_13      -1405.91    2158.04  -0.651  0.53888   
## Week_14       2414.63    1865.08   1.295  0.24303   
## Week_15       3325.83    1724.98   1.928  0.10212   
## Week_16       1678.40    1529.77   1.097  0.31464   
## Week_17      -7583.73    1677.73  -4.520  0.00402 **
## Week_18       1082.16    1199.72   0.902  0.40181   
## Week_19       1245.47    1143.83   1.089  0.31801   
## Week_20       1453.33    1058.23   1.373  0.21875   
## Week_21        753.84    1233.68   0.611  0.56358   
## Week_22      -2476.33    1412.64  -1.753  0.13015   
## Week_23        189.76    1180.52   0.161  0.87757   
## Week_24       1236.00    1381.83   0.894  0.40552   
## Week_25      -2461.33    1228.22  -2.004  0.09192 . 
## Week_26        919.70     437.73   2.101  0.08036 . 
## Week_27       1493.06    2075.23   0.719  0.49890   
## Week_28        533.91    2409.26   0.222  0.83197   
## Week_29       2307.32    3006.35   0.767  0.47191   
## Week_30      -2755.85    2359.70  -1.168  0.28716   
## Week_31        149.63    2036.58   0.073  0.94382   
## Week_32        439.09    3503.60   0.125  0.90436   
## Week_33       3293.80    2607.92   1.263  0.25345   
## Week_34       4976.79    4042.92   1.231  0.26439   
## Week_35       4389.25    2494.98   1.759  0.12903   
## Week_36     -10722.99    2211.62  -4.848  0.00286 **
## Week_37       3373.03    1950.33   1.729  0.13445   
## Week_38       1223.21    1976.42   0.619  0.55873   
## Week_39       1973.64    2039.79   0.968  0.37063   
## Week_40       -761.51    2331.13  -0.327  0.75501   
## Week_41      -2030.78    2302.22  -0.882  0.41167   
## Week_42      -1113.27    2847.16  -0.391  0.70930   
## Week_43       1810.92    3104.29   0.583  0.58090   
## Week_44       1513.11    1344.14   1.126  0.30329   
## Week_45      -3075.01    2172.68  -1.415  0.20673   
## Week_46       -537.24    1668.22  -0.322  0.75835   
## Week_47       1197.76    1521.02   0.787  0.46097   
## Week_48        320.67    1242.05   0.258  0.80490   
## Week_49      -1484.16    1164.92  -1.274  0.24977   
## Week_50       2038.08    2029.22   1.004  0.35397   
## Week_51        951.15    1378.33   0.690  0.51594   
## Week_52       1096.07    1148.33   0.954  0.37669   
## Week_53      -1152.40     925.95  -1.245  0.25970   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 12820 on 6 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.953,  Adjusted R-squared:  0.5378 
## F-statistic: 2.295 on 53 and 6 DF,  p-value: 0.1483

Abbotsford monthly

## [1] "There are 6  NA in the matrix X in Abbotsford station"
## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -83128 -40055  -1379  28889 110283 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 139811.0     7999.8  17.477   <2e-16 ***
## Month_1        521.0      884.1   0.589   0.5583    
## Month_2       -913.1     1016.1  -0.899   0.3732    
## Month_3        997.3      785.2   1.270   0.2101    
## Month_4       1051.4      607.8   1.730   0.0900 .  
## Month_5        936.8      511.1   1.833   0.0729 .  
## Month_6        621.2      320.9   1.936   0.0587 .  
## Month_7       1063.9      478.5   2.223   0.0308 *  
## Month_8       1917.5     1178.1   1.628   0.1100    
## Month_9       4248.3     1656.4   2.565   0.0134 *  
## Month_10     -2634.4     2914.7  -0.904   0.3705    
## Month_11     -1132.8     2020.3  -0.561   0.5776    
## Month_12       415.0     1048.2   0.396   0.6939    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 47600 on 49 degrees of freedom
## Multiple R-squared:  0.4567, Adjusted R-squared:  0.3237 
## F-statistic: 3.433 on 12 and 49 DF,  p-value: 0.001068

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -10085.2  -3371.7    504.3   3570.7  11400.2 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 24425.49     919.85  26.554   <2e-16 ***
## Month_1       -49.89     101.66  -0.491   0.6258    
## Month_2       -29.44     116.83  -0.252   0.8021    
## Month_3       199.03      90.29   2.204   0.0322 *  
## Month_4       120.83      69.89   1.729   0.0901 .  
## Month_5        97.11      58.77   1.652   0.1048    
## Month_6        18.59      36.90   0.504   0.6167    
## Month_7        63.99      55.02   1.163   0.2505    
## Month_8       311.02     135.46   2.296   0.0260 *  
## Month_9       339.10     190.46   1.780   0.0812 .  
## Month_10     -445.52     335.15  -1.329   0.1899    
## Month_11     -236.64     232.31  -1.019   0.3134    
## Month_12       54.12     120.53   0.449   0.6554    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5474 on 49 degrees of freedom
## Multiple R-squared:  0.3811, Adjusted R-squared:  0.2296 
## F-statistic: 2.515 on 12 and 49 DF,  p-value: 0.01158

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -31122  -8239   -518   7236  32357 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 60095.97    2409.55  24.941   <2e-16 ***
## Month_1       191.94     266.29   0.721   0.4745    
## Month_2      -270.34     306.04  -0.883   0.3814    
## Month_3       383.27     236.50   1.621   0.1115    
## Month_4       244.95     183.08   1.338   0.1871    
## Month_5       179.89     153.95   1.169   0.2483    
## Month_6       242.49      96.66   2.509   0.0155 *  
## Month_7       369.64     144.12   2.565   0.0134 *  
## Month_8       912.49     354.85   2.572   0.0132 *  
## Month_9       934.74     498.91   1.874   0.0670 .  
## Month_10    -1069.26     877.91  -1.218   0.2291    
## Month_11     -405.27     608.52  -0.666   0.5085    
## Month_12      359.04     315.73   1.137   0.2610    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 14340 on 49 degrees of freedom
## Multiple R-squared:  0.493,  Adjusted R-squared:  0.3689 
## F-statistic: 3.971 on 12 and 49 DF,  p-value: 0.0002775

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -16719.9  -4951.4    841.6   4278.2  14175.1 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 92702.49    1276.14  72.643  < 2e-16 ***
## Month_1       125.12     141.03   0.887 0.379328    
## Month_2       -19.87     162.09  -0.123 0.902953    
## Month_3       330.37     125.26   2.638 0.011158 *  
## Month_4       115.13      96.96   1.187 0.240819    
## Month_5       -77.89      81.53  -0.955 0.344081    
## Month_6        14.04      51.19   0.274 0.785021    
## Month_7       301.68      76.33   3.953 0.000248 ***
## Month_8      -233.37     187.93  -1.242 0.220240    
## Month_9       329.03     264.23   1.245 0.218975    
## Month_10     -398.92     464.96  -0.858 0.395088    
## Month_11      745.00     322.28   2.312 0.025044 *  
## Month_12      -89.07     167.22  -0.533 0.596675    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 7594 on 49 degrees of freedom
## Multiple R-squared:  0.4863, Adjusted R-squared:  0.3605 
## F-statistic: 3.865 on 12 and 49 DF,  p-value: 0.0003605

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -12660.6  -3094.1    227.8   2645.3  12989.5 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 19311.52     958.64  20.145   <2e-16 ***
## Month_1       -32.93     105.94  -0.311   0.7572    
## Month_2       -66.48     121.76  -0.546   0.5876    
## Month_3       142.65      94.09   1.516   0.1359    
## Month_4        93.74      72.84   1.287   0.2042    
## Month_5       110.53      61.25   1.805   0.0773 .  
## Month_6        49.61      38.45   1.290   0.2030    
## Month_7        68.37      57.34   1.192   0.2388    
## Month_8       370.36     141.18   2.623   0.0116 *  
## Month_9       246.75     198.49   1.243   0.2197    
## Month_10     -445.42     349.28  -1.275   0.2082    
## Month_11     -217.27     242.10  -0.897   0.3739    
## Month_12      102.03     125.61   0.812   0.4206    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5705 on 49 degrees of freedom
## Multiple R-squared:  0.3678, Adjusted R-squared:  0.213 
## F-statistic: 2.376 on 12 and 49 DF,  p-value: 0.01669

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11931.2  -3416.9     40.2   2467.4  17139.0 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 27981.612   1068.006  26.200   <2e-16 ***
## Month_1      -134.482    118.031  -1.139   0.2601    
## Month_2      -140.207    135.650  -1.034   0.3064    
## Month_3       128.518    104.827   1.226   0.2261    
## Month_4        -4.936     81.148  -0.061   0.9517    
## Month_5        63.461     68.235   0.930   0.3569    
## Month_6        24.973     42.841   0.583   0.5626    
## Month_7       -11.757     63.879  -0.184   0.8547    
## Month_8       274.108    157.282   1.743   0.0876 .  
## Month_9        95.019    221.137   0.430   0.6693    
## Month_10      177.198    389.125   0.455   0.6509    
## Month_11      114.656    269.721   0.425   0.6726    
## Month_12       84.667    139.945   0.605   0.5480    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6355 on 49 degrees of freedom
## Multiple R-squared:  0.1769, Adjusted R-squared:  -0.02462 
## F-statistic: 0.8778 on 12 and 49 DF,  p-value: 0.5741

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -31537  -7471   2092   9153  29061 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 67700.54    2429.09  27.871  < 2e-16 ***
## Month_1      -125.34     268.45  -0.467  0.64264    
## Month_2       -66.19     308.52  -0.215  0.83103    
## Month_3       302.17     238.42   1.267  0.21101    
## Month_4       286.12     184.56   1.550  0.12752    
## Month_5        52.63     155.20   0.339  0.73598    
## Month_6         4.35      97.44   0.045  0.96458    
## Month_7       -46.82     145.29  -0.322  0.74861    
## Month_8       594.42     357.73   1.662  0.10296    
## Month_9      1551.98     502.96   3.086  0.00334 ** 
## Month_10    -1242.53     885.03  -1.404  0.16664    
## Month_11      264.68     613.46   0.431  0.66803    
## Month_12     -208.75     318.29  -0.656  0.51499    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 14450 on 49 degrees of freedom
## Multiple R-squared:  0.3792, Adjusted R-squared:  0.2272 
## F-statistic: 2.495 on 12 and 49 DF,  p-value: 0.01222

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -17820.0  -6968.2   -405.4   5302.3  20617.2 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 43135.53    1619.08  26.642   <2e-16 ***
## Month_1       -44.55     178.93  -0.249   0.8044    
## Month_2        47.11     205.64   0.229   0.8198    
## Month_3       207.05     158.92   1.303   0.1987    
## Month_4        98.80     123.02   0.803   0.4258    
## Month_5       130.06     103.44   1.257   0.2146    
## Month_6        10.29      64.95   0.159   0.8747    
## Month_7        11.01      96.84   0.114   0.9099    
## Month_8       263.14     238.44   1.104   0.2752    
## Month_9       599.14     335.24   1.787   0.0801 .  
## Month_10     -107.63     589.91  -0.182   0.8560    
## Month_11     -349.29     408.89  -0.854   0.3971    
## Month_12       15.50     212.15   0.073   0.9421    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9635 on 49 degrees of freedom
## Multiple R-squared:  0.1837, Adjusted R-squared:  -0.01622 
## F-statistic: 0.9188 on 12 and 49 DF,  p-value: 0.5357

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -27165  -9654    295   7836  37911 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 42305.30    2599.62  16.274  < 2e-16 ***
## Month_1        92.96     287.30   0.324  0.74764    
## Month_2      -190.45     330.18  -0.577  0.56672    
## Month_3       570.16     255.16   2.235  0.03004 *  
## Month_4       244.04     197.52   1.236  0.22253    
## Month_5       198.78     166.09   1.197  0.23713    
## Month_6       202.15     104.28   1.939  0.05833 .  
## Month_7       239.27     155.49   1.539  0.13027    
## Month_8       803.04     382.84   2.098  0.04112 *  
## Month_9      1796.15     538.27   3.337  0.00162 ** 
## Month_10    -1200.40     947.16  -1.267  0.21102    
## Month_11       74.77     656.52   0.114  0.90979    
## Month_12      263.92     340.64   0.775  0.44219    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15470 on 49 degrees of freedom
## Multiple R-squared:  0.5022, Adjusted R-squared:  0.3803 
## F-statistic:  4.12 on 12 and 49 DF,  p-value: 0.0001929

Abbotsford monthly

## [1] "There are 7  NA in the matrix X in Kelowna station"
## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -97125 -39427  -8252  36192  95814 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 166461.3     9204.8  18.084   <2e-16 ***
## Month_1       -584.5     1010.2  -0.579    0.566    
## Month_2      -1794.7     1137.4  -1.578    0.121    
## Month_3       1236.4      917.6   1.347    0.184    
## Month_4       -183.6     1047.9  -0.175    0.862    
## Month_5        654.3      617.5   1.060    0.295    
## Month_6        441.2      569.6   0.775    0.442    
## Month_7        235.5     1024.4   0.230    0.819    
## Month_8       5077.8     3179.3   1.597    0.117    
## Month_9       6652.6     3152.1   2.111    0.040 *  
## Month_10     -3069.9     3334.4  -0.921    0.362    
## Month_11       418.4     1427.3   0.293    0.771    
## Month_12      -453.8      994.0  -0.457    0.650    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 53640 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.3101, Adjusted R-squared:  0.1377 
## F-statistic: 1.798 on 12 and 48 DF,  p-value: 0.0755

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11224.6  -3693.7    300.7   3662.8  11372.9 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 26403.302    948.583  27.834   <2e-16 ***
## Month_1      -200.357    104.108  -1.925   0.0602 .  
## Month_2      -223.187    117.207  -1.904   0.0629 .  
## Month_3       174.251     94.562   1.843   0.0716 .  
## Month_4       -38.479    107.990  -0.356   0.7232    
## Month_5       112.974     63.637   1.775   0.0822 .  
## Month_6         1.435     58.699   0.024   0.9806    
## Month_7       -28.891    105.571  -0.274   0.7855    
## Month_8       669.822    327.639   2.044   0.0464 *  
## Month_9       433.011    324.832   1.333   0.1888    
## Month_10     -215.774    343.622  -0.628   0.5330    
## Month_11      -84.118    147.083  -0.572   0.5701    
## Month_12      -12.822    102.433  -0.125   0.9009    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5528 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.3804, Adjusted R-squared:  0.2255 
## F-statistic: 2.455 on 12 and 48 DF,  p-value: 0.01382

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -31413 -12170  -2894   9570  31001 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 68017.23    2788.52  24.392   <2e-16 ***
## Month_1      -367.68     306.04  -1.201   0.2355    
## Month_2      -626.16     344.55  -1.817   0.0754 .  
## Month_3       559.18     277.98   2.012   0.0499 *  
## Month_4      -273.11     317.45  -0.860   0.3939    
## Month_5       144.34     187.07   0.772   0.4442    
## Month_6       168.89     172.56   0.979   0.3326    
## Month_7       350.62     310.34   1.130   0.2642    
## Month_8      1469.29     963.15   1.526   0.1337    
## Month_9      1916.71     954.90   2.007   0.0504 .  
## Month_10     -343.77    1010.13  -0.340   0.7351    
## Month_11       73.32     432.38   0.170   0.8661    
## Month_12       78.94     301.12   0.262   0.7943    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 16250 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.3577, Adjusted R-squared:  0.1971 
## F-statistic: 2.227 on 12 and 48 DF,  p-value: 0.02505

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -14153  -5490  -1262   5376  22646 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 94200.881   1622.263  58.068   <2e-16 ***
## Month_1        54.751    178.045   0.308    0.760    
## Month_2      -165.778    200.447  -0.827    0.412    
## Month_3       157.115    161.720   0.972    0.336    
## Month_4        78.341    184.683   0.424    0.673    
## Month_5         4.315    108.833   0.040    0.969    
## Month_6      -113.398    100.387  -1.130    0.264    
## Month_7       208.230    180.547   1.153    0.254    
## Month_8       574.145    560.326   1.025    0.311    
## Month_9       182.230    555.527   0.328    0.744    
## Month_10     -940.413    587.661  -1.600    0.116    
## Month_11      347.187    251.542   1.380    0.174    
## Month_12     -104.652    175.180  -0.597    0.553    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9453 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.2174, Adjusted R-squared:  0.02179 
## F-statistic: 1.111 on 12 and 48 DF,  p-value: 0.3733

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11209.8  -3796.6   -377.4   3152.6  15151.7 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 21464.44    1038.86  20.662   <2e-16 ***
## Month_1      -140.29     114.02  -1.230   0.2245    
## Month_2      -213.08     128.36  -1.660   0.1034    
## Month_3       180.26     103.56   1.741   0.0882 .  
## Month_4      -174.68     118.27  -1.477   0.1462    
## Month_5        54.74      69.69   0.785   0.4361    
## Month_6        54.42      64.29   0.847   0.4015    
## Month_7       -18.26     115.62  -0.158   0.8752    
## Month_8       512.06     358.82   1.427   0.1600    
## Month_9       610.33     355.75   1.716   0.0927 .  
## Month_10     -258.02     376.32  -0.686   0.4962    
## Month_11      -74.84     161.08  -0.465   0.6443    
## Month_12      -17.72     112.18  -0.158   0.8751    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6054 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.3007, Adjusted R-squared:  0.1259 
## F-statistic:  1.72 on 12 and 48 DF,  p-value: 0.09187

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13918.5  -3792.6   -126.6   1995.7  16782.0 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 29365.79    1131.82  25.946   <2e-16 ***
## Month_1      -107.59     124.22  -0.866    0.391    
## Month_2       -88.39     139.85  -0.632    0.530    
## Month_3        83.94     112.83   0.744    0.461    
## Month_4        48.09     128.85   0.373    0.711    
## Month_5       -77.52      75.93  -1.021    0.312    
## Month_6       112.42      70.04   1.605    0.115    
## Month_7       -23.60     125.96  -0.187    0.852    
## Month_8       236.91     390.93   0.606    0.547    
## Month_9       166.80     387.58   0.430    0.669    
## Month_10      172.64     410.00   0.421    0.676    
## Month_11     -107.09     175.50  -0.610    0.545    
## Month_12       28.53     122.22   0.233    0.816    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 6595 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.1298, Adjusted R-squared:  -0.08779 
## F-statistic: 0.5965 on 12 and 48 DF,  p-value: 0.8341

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -37202  -7839   1099   8652  23218 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 71851.85    2561.83  28.047   <2e-16 ***
## Month_1      -405.20     281.16  -1.441   0.1560    
## Month_2      -577.77     316.54  -1.825   0.0742 .  
## Month_3        14.96     255.38   0.059   0.9535    
## Month_4       344.61     291.65   1.182   0.2432    
## Month_5       341.17     171.87   1.985   0.0529 .  
## Month_6        25.43     158.53   0.160   0.8732    
## Month_7      -184.93     285.11  -0.649   0.5197    
## Month_8      2262.38     884.85   2.557   0.0138 *  
## Month_9       899.62     877.27   1.025   0.3103    
## Month_10     -255.89     928.02  -0.276   0.7839    
## Month_11      410.47     397.23   1.033   0.3066    
## Month_12       42.58     276.64   0.154   0.8783    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 14930 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.3514, Adjusted R-squared:  0.1892 
## F-statistic: 2.167 on 12 and 48 DF,  p-value: 0.02931

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -14682.6  -7423.7   -193.1   6081.1  18921.7 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 45912.01    1489.48  30.824  < 2e-16 ***
## Month_1      -162.22     163.47  -0.992  0.32600    
## Month_2      -150.52     184.04  -0.818  0.41748    
## Month_3       162.41     148.48   1.094  0.27950    
## Month_4       350.11     169.57   2.065  0.04437 *  
## Month_5       269.45      99.92   2.697  0.00963 ** 
## Month_6       -36.11      92.17  -0.392  0.69699    
## Month_7       -17.82     165.77  -0.107  0.91485    
## Month_8       224.31     514.46   0.436  0.66479    
## Month_9       463.59     510.06   0.909  0.36794    
## Month_10      546.11     539.56   1.012  0.31655    
## Month_11       42.36     230.95   0.183  0.85524    
## Month_12     -178.26     160.84  -1.108  0.27326    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8679 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.335,  Adjusted R-squared:  0.1687 
## F-statistic: 2.015 on 12 and 48 DF,  p-value: 0.04345

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
## -36558  -7983   -761   7877  32691 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 50249.40    2897.35  17.343   <2e-16 ***
## Month_1      -353.10     317.99  -1.110   0.2723    
## Month_2      -753.93     358.00  -2.106   0.0405 *  
## Month_3       344.17     288.83   1.192   0.2393    
## Month_4       -26.56     329.84  -0.081   0.9362    
## Month_5       393.99     194.37   2.027   0.0482 *  
## Month_6       137.54     179.29   0.767   0.4468    
## Month_7       183.98     322.45   0.571   0.5710    
## Month_8      2159.48    1000.74   2.158   0.0360 *  
## Month_9      2334.12     992.17   2.353   0.0228 *  
## Month_10     -803.95    1049.56  -0.766   0.4474    
## Month_11      321.73     449.25   0.716   0.4774    
## Month_12      190.80     312.87   0.610   0.5448    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 16880 on 48 degrees of freedom
##   (1 observation deleted due to missingness)
## Multiple R-squared:  0.4155, Adjusted R-squared:  0.2694 
## F-statistic: 2.844 on 12 and 48 DF,  p-value: 0.005024

linear reg for yield VS daily Max Temp

Abbotsford

## [1] "Results for crop: Apples"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -27887.8  -8791.8   -970.2   9462.8  30817.2 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -379410.47  216422.90  -1.753   0.1177  
## Week_1         5569.15    3867.69   1.440   0.1879  
## Week_2         4633.31    4580.18   1.012   0.3413  
## Week_3        -3710.64    4951.29  -0.749   0.4751  
## Week_4           27.95    4122.76   0.007   0.9948  
## Week_5          487.06    4704.67   0.104   0.9201  
## Week_6        -1109.62    6349.16  -0.175   0.8656  
## Week_7         2491.88    5178.18   0.481   0.6432  
## Week_8         1956.54    8225.02   0.238   0.8180  
## Week_9        -2324.53    4514.65  -0.515   0.6206  
## Week_10       -3040.07    7166.04  -0.424   0.6826  
## Week_11      -15492.00   11097.32  -1.396   0.2002  
## Week_12        6499.98    7199.61   0.903   0.3930  
## Week_13        8247.42   11298.69   0.730   0.4862  
## Week_14       -9458.74   16998.02  -0.556   0.5931  
## Week_15        8600.07   10328.70   0.833   0.4292  
## Week_16       -1342.51    6477.99  -0.207   0.8410  
## Week_17       11582.98    7095.79   1.632   0.1412  
## Week_18        6484.74    7605.25   0.853   0.4186  
## Week_19        1256.56    6470.79   0.194   0.8509  
## Week_20        7659.30    7092.90   1.080   0.3117  
## Week_21        2722.31    7773.04   0.350   0.7352  
## Week_22       -4391.71    7022.84  -0.625   0.5492  
## Week_23         181.00    6893.98   0.026   0.9797  
## Week_24       -7746.16    6029.18  -1.285   0.2348  
## Week_25        2684.34    7933.91   0.338   0.7438  
## Week_26        1207.84    7960.36   0.152   0.8832  
## Week_27       10662.66   11377.60   0.937   0.3761  
## Week_28        3922.51    9126.18   0.430   0.6787  
## Week_29      -12120.23    9269.33  -1.308   0.2273  
## Week_30        8497.35    8158.22   1.042   0.3281  
## Week_31       10183.10    7471.30   1.363   0.2100  
## Week_32       -6251.69    4441.55  -1.408   0.1969  
## Week_33      -12660.54    8296.48  -1.526   0.1655  
## Week_34       24884.44    8528.16   2.918   0.0194 *
## Week_35       -4741.30    5859.62  -0.809   0.4418  
## Week_36        3778.39    7869.29   0.480   0.6440  
## Week_37        2959.59    9376.17   0.316   0.7603  
## Week_38         477.54    8461.64   0.056   0.9564  
## Week_39      -11950.24    8350.59  -1.431   0.1903  
## Week_40        6703.27    7324.00   0.915   0.3868  
## Week_41      -10685.91    8618.50  -1.240   0.2502  
## Week_42        8432.17    8595.78   0.981   0.3553  
## Week_43        1782.38    6710.56   0.266   0.7973  
## Week_44       -4602.96    4994.26  -0.922   0.3837  
## Week_45      -10205.91    7467.38  -1.367   0.2089  
## Week_46        9118.57    6963.67   1.309   0.2267  
## Week_47       -2333.68    4243.52  -0.550   0.5974  
## Week_48         751.76    7298.11   0.103   0.9205  
## Week_49         697.45    3835.69   0.182   0.8602  
## Week_50       -2093.30    4034.65  -0.519   0.6179  
## Week_51       -4463.51    4658.36  -0.958   0.3660  
## Week_52        6020.65    6413.27   0.939   0.3753  
## Week_53       -1509.30    3352.33  -0.450   0.6645  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 39000 on 8 degrees of freedom
## Multiple R-squared:  0.9405, Adjusted R-squared:  0.5459 
## F-statistic: 2.384 on 53 and 8 DF,  p-value: 0.09579

## [1] "Results for crop: Barley"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -4204.1 -1123.1   117.2  1306.2  3614.9 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -13226.592  28152.253  -0.470   0.6510  
## Week_1        -206.202    503.109  -0.410   0.6927  
## Week_2         471.703    595.789   0.792   0.4514  
## Week_3        -430.418    644.063  -0.668   0.5228  
## Week_4         460.727    536.288   0.859   0.4153  
## Week_5        -353.637    611.982  -0.578   0.5793  
## Week_6         861.448    825.897   1.043   0.3274  
## Week_7         267.191    673.576   0.397   0.7020  
## Week_8        -383.405   1069.908  -0.358   0.7294  
## Week_9         484.765    587.265   0.825   0.4330  
## Week_10      -2000.691    932.157  -2.146   0.0641 .
## Week_11       -971.361   1443.538  -0.673   0.5200  
## Week_12       1229.279    936.524   1.313   0.2257  
## Week_13       -672.262   1469.731  -0.457   0.6595  
## Week_14       -642.650   2211.100  -0.291   0.7787  
## Week_15       2896.384   1343.555   2.156   0.0632 .
## Week_16       -314.541    842.656  -0.373   0.7186  
## Week_17       1648.437    923.019   1.786   0.1119  
## Week_18        755.261    989.290   0.763   0.4671  
## Week_19       1460.848    841.719   1.736   0.1209  
## Week_20        550.243    922.643   0.596   0.5674  
## Week_21         -2.594   1011.116  -0.003   0.9980  
## Week_22        959.620    913.529   1.050   0.3242  
## Week_23       -113.083    896.768  -0.126   0.9028  
## Week_24      -1104.231    784.275  -1.408   0.1968  
## Week_25       -914.571   1032.042  -0.886   0.4014  
## Week_26        772.857   1035.482   0.746   0.4768  
## Week_27       1194.739   1479.997   0.807   0.4429  
## Week_28       -243.264   1187.132  -0.205   0.8428  
## Week_29      -2210.946   1205.753  -1.834   0.1041  
## Week_30        265.191   1061.220   0.250   0.8090  
## Week_31        226.036    971.866   0.233   0.8219  
## Week_32        515.944    577.756   0.893   0.3979  
## Week_33       -795.922   1079.205  -0.738   0.4819  
## Week_34       3514.440   1109.341   3.168   0.0132 *
## Week_35       -396.296    762.219  -0.520   0.6172  
## Week_36      -1025.491   1023.636  -1.002   0.3458  
## Week_37       -345.374   1219.650  -0.283   0.7842  
## Week_38       1584.012   1100.689   1.439   0.1881  
## Week_39      -1461.904   1086.243  -1.346   0.2152  
## Week_40        778.879    952.705   0.818   0.4373  
## Week_41      -1850.641   1121.093  -1.651   0.1374  
## Week_42         -3.340   1118.138  -0.003   0.9977  
## Week_43         40.480    872.908   0.046   0.9641  
## Week_44       -631.555    649.653  -0.972   0.3595  
## Week_45      -2162.071    971.355  -2.226   0.0567 .
## Week_46       1061.800    905.833   1.172   0.2748  
## Week_47       -344.553    551.996  -0.624   0.5499  
## Week_48       -614.060    949.336  -0.647   0.5359  
## Week_49         90.030    498.946   0.180   0.8613  
## Week_50        125.258    524.826   0.239   0.8174  
## Week_51        -41.222    605.959  -0.068   0.9474  
## Week_52        634.156    834.237   0.760   0.4690  
## Week_53       -183.356    436.071  -0.420   0.6852  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5074 on 8 degrees of freedom
## Multiple R-squared:  0.9132, Adjusted R-squared:  0.3381 
## F-statistic: 1.588 on 53 and 8 DF,  p-value: 0.2509

## [1] "Results for crop: Maize (corn)"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -8212.3 -3126.3  -288.8  2799.6  7937.3 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -95390.10   59691.64  -1.598   0.1487  
## Week_1         750.61    1066.75   0.704   0.5016  
## Week_2        1107.53    1263.26   0.877   0.4062  
## Week_3       -1040.10    1365.62  -0.762   0.4681  
## Week_4        1237.90    1137.10   1.089   0.3080  
## Week_5       -1064.53    1297.60  -0.820   0.4358  
## Week_6         594.68    1751.16   0.340   0.7429  
## Week_7         530.56    1428.19   0.371   0.7199  
## Week_8         366.48    2268.54   0.162   0.8757  
## Week_9        -624.03    1245.19  -0.501   0.6298  
## Week_10      -2899.75    1976.47  -1.467   0.1805  
## Week_11      -4937.88    3060.75  -1.613   0.1453  
## Week_12       1578.46    1985.73   0.795   0.4496  
## Week_13       2252.13    3116.29   0.723   0.4905  
## Week_14      -2017.69    4688.23  -0.430   0.6783  
## Week_15       2250.45    2848.76   0.790   0.4523  
## Week_16        447.49    1786.70   0.250   0.8085  
## Week_17       4306.02    1957.09   2.200   0.0590 .
## Week_18       1908.14    2097.61   0.910   0.3896  
## Week_19        991.73    1784.71   0.556   0.5936  
## Week_20       1918.57    1956.29   0.981   0.3555  
## Week_21        -42.95    2143.88  -0.020   0.9845  
## Week_22        168.93    1936.97   0.087   0.9326  
## Week_23       -510.02    1901.43  -0.268   0.7953  
## Week_24      -2308.19    1662.91  -1.388   0.2026  
## Week_25       -978.05    2188.25  -0.447   0.6668  
## Week_26       1289.66    2195.55   0.587   0.5731  
## Week_27       4283.96    3138.06   1.365   0.2094  
## Week_28       1816.04    2517.09   0.721   0.4912  
## Week_29      -3301.41    2556.58  -1.291   0.2326  
## Week_30       2132.15    2250.12   0.948   0.3711  
## Week_31       1333.15    2060.66   0.647   0.5358  
## Week_32       -970.70    1225.02  -0.792   0.4510  
## Week_33      -2056.35    2288.25  -0.899   0.3951  
## Week_34       7513.20    2352.15   3.194   0.0127 *
## Week_35      -2363.57    1616.14  -1.462   0.1818  
## Week_36       1555.51    2170.43   0.717   0.4940  
## Week_37      -1101.11    2586.04  -0.426   0.6815  
## Week_38       1467.94    2333.81   0.629   0.5469  
## Week_39      -4355.88    2303.18  -1.891   0.0952 .
## Week_40       1979.71    2020.03   0.980   0.3558  
## Week_41      -2932.57    2377.07  -1.234   0.2523  
## Week_42       2021.47    2370.80   0.853   0.4186  
## Week_43       -137.38    1850.84  -0.074   0.9427  
## Week_44       -533.27    1377.47  -0.387   0.7087  
## Week_45      -4128.94    2059.58  -2.005   0.0799 .
## Week_46       3252.47    1920.65   1.693   0.1288  
## Week_47       -977.19    1170.40  -0.835   0.4280  
## Week_48         55.03    2012.89   0.027   0.9789  
## Week_49        -99.20    1057.92  -0.094   0.9276  
## Week_50        303.35    1112.80   0.273   0.7921  
## Week_51      -1293.32    1284.82  -1.007   0.3436  
## Week_52       2003.27    1768.85   1.133   0.2902  
## Week_53      -1053.95     924.61  -1.140   0.2873  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10760 on 8 degrees of freedom
## Multiple R-squared:  0.9534, Adjusted R-squared:  0.6447 
## F-statistic: 3.089 on 53 and 8 DF,  p-value: 0.04663

## [1] "Results for crop: Peaches and nectarines"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5074.5 -1479.5    83.5  1702.3  5149.9 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -2186.260  31963.754  -0.068   0.9471  
## Week_1        934.411    571.224   1.636   0.1405  
## Week_2         -5.987    676.452  -0.009   0.9932  
## Week_3       -303.844    731.262  -0.416   0.6887  
## Week_4       -341.289    608.895  -0.561   0.5905  
## Week_5        -19.539    694.838  -0.028   0.9783  
## Week_6       -437.527    937.715  -0.467   0.6532  
## Week_7       -468.809    764.771  -0.613   0.5569  
## Week_8       -149.493   1214.762  -0.123   0.9051  
## Week_9         -3.953    666.774  -0.006   0.9954  
## Week_10      -192.018   1058.361  -0.181   0.8605  
## Week_11      -120.229   1638.977  -0.073   0.9433  
## Week_12       158.598   1063.319   0.149   0.8851  
## Week_13       704.678   1668.717   0.422   0.6839  
## Week_14      2715.992   2510.458   1.082   0.3108  
## Week_15      -328.866   1525.457  -0.216   0.8347  
## Week_16       119.674    956.743   0.125   0.9035  
## Week_17      1498.923   1047.986   1.430   0.1905  
## Week_18     -1482.445   1123.229  -1.320   0.2234  
## Week_19      -465.128    955.679  -0.487   0.6395  
## Week_20       943.113   1047.558   0.900   0.3943  
## Week_21      -148.495   1148.010  -0.129   0.9003  
## Week_22      -286.892   1037.211  -0.277   0.7891  
## Week_23       638.609   1018.180   0.627   0.5480  
## Week_24      -992.207    890.457  -1.114   0.2975  
## Week_25      1731.828   1171.769   1.478   0.1777  
## Week_26     -1720.659   1175.674  -1.464   0.1815  
## Week_27      2407.086   1680.372   1.432   0.1899  
## Week_28      1175.362   1347.856   0.872   0.4086  
## Week_29       245.021   1368.999   0.179   0.8624  
## Week_30       675.510   1204.897   0.561   0.5904  
## Week_31      1373.139   1103.446   1.244   0.2486  
## Week_32      -115.916    655.978  -0.177   0.8641  
## Week_33     -2464.103   1225.317  -2.011   0.0792 .
## Week_34       910.440   1259.533   0.723   0.4904  
## Week_35       -15.881    865.415  -0.018   0.9858  
## Week_36     -1366.769   1162.225  -1.176   0.2734  
## Week_37      -259.754   1384.777  -0.188   0.8559  
## Week_38       293.554   1249.710   0.235   0.8202  
## Week_39       -12.326   1233.308  -0.010   0.9923  
## Week_40      1340.438   1081.690   1.239   0.2504  
## Week_41      -266.946   1272.877  -0.210   0.8391  
## Week_42       840.961   1269.521   0.662   0.5263  
## Week_43      1257.420    991.090   1.269   0.2402  
## Week_44     -1471.160    737.609  -1.994   0.0812 .
## Week_45     -1050.131   1102.866  -0.952   0.3689  
## Week_46      2202.746   1028.472   2.142   0.0646 .
## Week_47      -198.656    626.730  -0.317   0.7594  
## Week_48      1264.609   1077.866   1.173   0.2744  
## Week_49       355.754    566.498   0.628   0.5475  
## Week_50       334.252    595.882   0.561   0.5902  
## Week_51      -546.703    687.999  -0.795   0.4498  
## Week_52       109.568    947.184   0.116   0.9108  
## Week_53       438.117    495.110   0.885   0.4020  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5761 on 8 degrees of freedom
## Multiple R-squared:  0.9517, Adjusted R-squared:  0.632 
## F-statistic: 2.976 on 53 and 8 DF,  p-value: 0.05191

## [1] "Results for crop: Wheat"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3638.5 -1138.7   -64.5  1057.1  3613.5 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -13620.06   26181.53  -0.520   0.6170  
## Week_1        -170.93     467.89  -0.365   0.7243  
## Week_2         387.58     554.08   0.699   0.5041  
## Week_3        -766.01     598.98  -1.279   0.2368  
## Week_4         566.51     498.75   1.136   0.2889  
## Week_5        -374.77     569.14  -0.658   0.5287  
## Week_6         494.10     768.08   0.643   0.5380  
## Week_7         359.59     626.42   0.574   0.5817  
## Week_8        -433.02     995.01  -0.435   0.6749  
## Week_9         361.24     546.16   0.661   0.5269  
## Week_10      -1921.02     866.90  -2.216   0.0575 .
## Week_11      -1680.93    1342.49  -1.252   0.2459  
## Week_12       1524.00     870.97   1.750   0.1183  
## Week_13        574.84    1366.85   0.421   0.6851  
## Week_14      -2024.14    2056.32  -0.984   0.3538  
## Week_15       2290.80    1249.50   1.833   0.1041  
## Week_16       -644.50     783.67  -0.822   0.4347  
## Week_17       1634.33     858.41   1.904   0.0934 .
## Week_18       1213.25     920.04   1.319   0.2238  
## Week_19        868.42     782.80   1.109   0.2995  
## Week_20        972.18     858.06   1.133   0.2900  
## Week_21       -585.35     940.34  -0.622   0.5509  
## Week_22        460.18     849.58   0.542   0.6028  
## Week_23         68.34     833.99   0.082   0.9367  
## Week_24      -1212.66     729.37  -1.663   0.1350  
## Week_25       -953.90     959.80  -0.994   0.3494  
## Week_26        929.03     963.00   0.965   0.3629  
## Week_27        794.17    1376.39   0.577   0.5798  
## Week_28        634.97    1104.03   0.575   0.5810  
## Week_29      -2294.68    1121.35  -2.046   0.0749 .
## Week_30        403.28     986.93   0.409   0.6935  
## Week_31        689.49     903.83   0.763   0.4674  
## Week_32        241.33     537.31   0.449   0.6652  
## Week_33       -738.99    1003.66  -0.736   0.4826  
## Week_34       3245.97    1031.68   3.146   0.0137 *
## Week_35       -597.21     708.86  -0.842   0.4240  
## Week_36       -692.89     951.98  -0.728   0.4875  
## Week_37       -349.95    1134.27  -0.309   0.7656  
## Week_38       1247.04    1023.64   1.218   0.2578  
## Week_39      -1373.30    1010.20  -1.359   0.2111  
## Week_40        106.14     886.01   0.120   0.9076  
## Week_41      -1294.95    1042.61  -1.242   0.2494  
## Week_42        530.63    1039.87   0.510   0.6236  
## Week_43        222.70     811.80   0.274   0.7908  
## Week_44        -66.02     604.18  -0.109   0.9157  
## Week_45      -2097.31     903.36  -2.322   0.0488 *
## Week_46       1781.16     842.42   2.114   0.0674 .
## Week_47       -235.84     513.35  -0.459   0.6582  
## Week_48       -616.75     882.88  -0.699   0.5046  
## Week_49       -352.65     464.02  -0.760   0.4691  
## Week_50       -146.35     488.09  -0.300   0.7719  
## Week_51        150.73     563.54   0.267   0.7959  
## Week_52        206.51     775.84   0.266   0.7968  
## Week_53       -115.02     405.54  -0.284   0.7839  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4719 on 8 degrees of freedom
## Multiple R-squared:  0.9294, Adjusted R-squared:  0.4615 
## F-statistic: 1.987 on 53 and 8 DF,  p-value: 0.1517

## [1] "Results for crop: Wine"
## [1] "No data available for this crop."
## [1] "Results for crop: Blueberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -5846.3 -1290.8   -50.8  1531.9  4371.4 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept)  2614.52   33260.31   0.079   0.9393  
## Week_1       -677.65     594.40  -1.140   0.2872  
## Week_2       -459.24     703.89  -0.652   0.5324  
## Week_3       -386.17     760.92  -0.507   0.6255  
## Week_4       1072.94     633.59   1.693   0.1288  
## Week_5       -894.85     723.02  -1.238   0.2509  
## Week_6       -484.15     975.75  -0.496   0.6331  
## Week_7        745.73     795.79   0.937   0.3761  
## Week_8      -1011.55    1264.04  -0.800   0.4467  
## Week_9       -355.68     693.82  -0.513   0.6221  
## Week_10      -830.61    1101.29  -0.754   0.4723  
## Week_11       816.93    1705.46   0.479   0.6448  
## Week_12      1693.65    1106.45   1.531   0.1644  
## Week_13      -963.66    1736.41  -0.555   0.5941  
## Week_14      2934.10    2612.29   1.123   0.2939  
## Week_15      -766.97    1587.34  -0.483   0.6419  
## Week_16      1045.38     995.55   1.050   0.3244  
## Week_17      -227.59    1090.50  -0.209   0.8399  
## Week_18     -2037.50    1168.79  -1.743   0.1195  
## Week_19       358.32     994.44   0.360   0.7279  
## Week_20       377.12    1090.05   0.346   0.7383  
## Week_21     -1059.99    1194.58  -0.887   0.4008  
## Week_22     -1251.47    1079.28  -1.160   0.2797  
## Week_23        37.41    1059.48   0.035   0.9727  
## Week_24       706.22     926.58   0.762   0.4678  
## Week_25       801.80    1219.30   0.658   0.5293  
## Week_26       511.63    1223.36   0.418   0.6868  
## Week_27       -71.87    1748.53  -0.041   0.9682  
## Week_28      1418.16    1402.53   1.011   0.3415  
## Week_29       731.50    1424.53   0.514   0.6215  
## Week_30     -1858.69    1253.77  -1.482   0.1765  
## Week_31      -307.74    1148.21  -0.268   0.7955  
## Week_32        74.90     682.59   0.110   0.9153  
## Week_33      1348.41    1275.02   1.058   0.3211  
## Week_34       390.25    1310.62   0.298   0.7735  
## Week_35     -1038.43     900.52  -1.153   0.2821  
## Week_36      -347.90    1209.37  -0.288   0.7809  
## Week_37      -122.80    1440.95  -0.085   0.9342  
## Week_38       251.42    1300.40   0.193   0.8515  
## Week_39      -344.60    1283.34  -0.269   0.7951  
## Week_40      -416.53    1125.57  -0.370   0.7209  
## Week_41       476.62    1324.51   0.360   0.7283  
## Week_42      1964.90    1321.02   1.487   0.1752  
## Week_43     -1325.35    1031.29  -1.285   0.2347  
## Week_44      1780.50     767.53   2.320   0.0489 *
## Week_45     -1894.00    1147.60  -1.650   0.1375  
## Week_46       934.35    1070.19   0.873   0.4081  
## Week_47      1417.49     652.15   2.174   0.0615 .
## Week_48      -107.34    1121.59  -0.096   0.9261  
## Week_49      -844.77     589.48  -1.433   0.1897  
## Week_50      -468.68     620.05  -0.756   0.4714  
## Week_51       252.46     715.91   0.353   0.7335  
## Week_52     -1091.62     985.60  -1.108   0.3002  
## Week_53       177.79     515.19   0.345   0.7389  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 5994 on 8 degrees of freedom
## Multiple R-squared:  0.8805, Adjusted R-squared:  0.08847 
## F-statistic: 1.112 on 53 and 8 DF,  p-value: 0.4763

## [1] "Results for crop: Grapes"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -11813.4  -3030.8    397.2   3226.0  12447.3 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) 93315.0390 74777.6071   1.248   0.2474  
## Week_1       -419.4469  1336.3506  -0.314   0.7616  
## Week_2      -1433.2573  1582.5262  -0.906   0.3916  
## Week_3       2258.2339  1710.7507   1.320   0.2233  
## Week_4        472.4900  1424.4800   0.332   0.7486  
## Week_5      -1146.2948  1625.5386  -0.705   0.5007  
## Week_6        353.8557  2193.7364   0.161   0.8759  
## Week_7         16.4335  1789.1440   0.009   0.9929  
## Week_8      -1803.9206  2841.8755  -0.635   0.5433  
## Week_9       -480.1525  1559.8856  -0.308   0.7661  
## Week_10     -3795.2263  2475.9821  -1.533   0.1639  
## Week_11     -2046.9935  3834.3045  -0.534   0.6079  
## Week_12      1572.8965  2487.5815   0.632   0.5448  
## Week_13     -2297.9034  3903.8791  -0.589   0.5724  
## Week_14      3461.4017  5873.0915   0.589   0.5719  
## Week_15      6790.4379  3568.7313   1.903   0.0936 .
## Week_16      4154.3312  2238.2517   1.856   0.1005  
## Week_17      3397.8516  2451.7104   1.386   0.2032  
## Week_18     -1608.5163  2627.7381  -0.612   0.5574  
## Week_19       943.7657  2235.7629   0.422   0.6841  
## Week_20      1668.0157  2450.7102   0.681   0.5153  
## Week_21      -945.4573  2685.7118  -0.352   0.7339  
## Week_22         0.7152  2426.5036   0.000   0.9998  
## Week_23     -1077.3680  2381.9820  -0.452   0.6631  
## Week_24     -3291.8970  2083.1794  -1.580   0.1527  
## Week_25     -3647.3402  2741.2940  -1.331   0.2200  
## Week_26      4181.3355  2750.4315   1.520   0.1669  
## Week_27      2963.2074  3931.1454   0.754   0.4726  
## Week_28      1390.0122  3153.2425   0.441   0.6710  
## Week_29       400.7122  3202.7046   0.125   0.9035  
## Week_30     -1383.8310  2818.7972  -0.491   0.6367  
## Week_31     -3047.3280  2581.4560  -1.180   0.2717  
## Week_32       528.0668  1534.6270   0.344   0.7396  
## Week_33      -808.6604  2866.5675  -0.282   0.7850  
## Week_34      6494.5491  2946.6155   2.204   0.0586 .
## Week_35      1495.1868  2024.5950   0.739   0.4813  
## Week_36      -128.2266  2718.9666  -0.047   0.9635  
## Week_37     -5400.3101  3239.6164  -1.667   0.1341  
## Week_38      4013.8240  2923.6343   1.373   0.2070  
## Week_39     -6848.5002  2885.2634  -2.374   0.0450 *
## Week_40       350.0976  2530.5603   0.138   0.8934  
## Week_41     -2519.6301  2977.8319  -0.846   0.4221  
## Week_42      -677.9038  2969.9809  -0.228   0.8252  
## Week_43     -5285.3740  2318.6053  -2.280   0.0521 .
## Week_44      -552.8590  1725.5989  -0.320   0.7569  
## Week_45     -6062.1221  2580.1004  -2.350   0.0467 *
## Week_46      3191.7414  2406.0598   1.327   0.2213  
## Week_47      -176.6592  1466.2031  -0.120   0.9071  
## Week_48      1510.4028  2521.6136   0.599   0.5658  
## Week_49       743.4374  1325.2938   0.561   0.5902  
## Week_50      2045.2262  1394.0358   1.467   0.1805  
## Week_51     -1932.5901  1609.5402  -1.201   0.2642  
## Week_52      4028.7597  2215.8892   1.818   0.1066  
## Week_53     -2245.1934  1158.2854  -1.938   0.0886 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 13480 on 8 degrees of freedom
## Multiple R-squared:  0.9119, Adjusted R-squared:  0.3282 
## F-statistic: 1.562 on 53 and 8 DF,  p-value: 0.2595

## [1] "Results for crop: Raspberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -9762.3 -2100.8   230.9  2349.8  6195.7 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -61187.71   46168.70  -1.325   0.2217  
## Week_1        1141.71     825.08   1.384   0.2038  
## Week_2        2571.75     977.07   2.632   0.0301 *
## Week_3        -481.87    1056.24  -0.456   0.6604  
## Week_4        -107.62     879.49  -0.122   0.9056  
## Week_5        -212.14    1003.63  -0.211   0.8379  
## Week_6        -450.96    1354.44  -0.333   0.7477  
## Week_7        1304.39    1104.64   1.181   0.2716  
## Week_8        1800.95    1754.61   1.026   0.3347  
## Week_9       -1167.50     963.09  -1.212   0.2600  
## Week_10       1605.93    1528.70   1.051   0.3242  
## Week_11      -2342.20    2367.35  -0.989   0.3515  
## Week_12      -2007.14    1535.87  -1.307   0.2276  
## Week_13       1166.39    2410.31   0.484   0.6414  
## Week_14       4030.56    3626.13   1.112   0.2986  
## Week_15        193.04    2203.38   0.088   0.9323  
## Week_16       1030.72    1381.93   0.746   0.4771  
## Week_17        577.82    1513.72   0.382   0.7126  
## Week_18       1907.75    1622.40   1.176   0.2734  
## Week_19        513.95    1380.39   0.372   0.7193  
## Week_20      -1281.64    1513.10  -0.847   0.4216  
## Week_21       4363.44    1658.19   2.631   0.0301 *
## Week_22         41.49    1498.16   0.028   0.9786  
## Week_23      -2198.68    1470.67  -1.495   0.1733  
## Week_24       1860.18    1286.18   1.446   0.1861  
## Week_25        966.42    1692.51   0.571   0.5837  
## Week_26      -1731.03    1698.15  -1.019   0.3379  
## Week_27       2733.47    2427.14   1.126   0.2927  
## Week_28      -3773.68    1946.85  -1.938   0.0886 .
## Week_29        556.91    1977.39   0.282   0.7854  
## Week_30       1876.28    1740.36   1.078   0.3124  
## Week_31        369.58    1593.83   0.232   0.8225  
## Week_32       -600.33     947.50  -0.634   0.5440  
## Week_33      -2804.78    1769.86  -1.585   0.1517  
## Week_34       2074.56    1819.28   1.140   0.2871  
## Week_35      -2122.18    1250.01  -1.698   0.1280  
## Week_36       3432.87    1678.73   2.045   0.0751 .
## Week_37       1239.02    2000.18   0.619   0.5528  
## Week_38      -2025.65    1805.09  -1.122   0.2943  
## Week_39       -790.84    1781.40  -0.444   0.6688  
## Week_40       1590.43    1562.40   1.018   0.3385  
## Week_41       -368.28    1838.55  -0.200   0.8462  
## Week_42        451.98    1833.71   0.246   0.8115  
## Week_43       -110.83    1431.54  -0.077   0.9402  
## Week_44       -907.94    1065.41  -0.852   0.4189  
## Week_45       -646.03    1592.99  -0.406   0.6957  
## Week_46      -1443.39    1485.53  -0.972   0.3597  
## Week_47       -904.31     905.25  -0.999   0.3471  
## Week_48       1098.79    1556.88   0.706   0.5004  
## Week_49       1208.57     818.25   1.477   0.1779  
## Week_50      -1014.99     860.70  -1.179   0.2722  
## Week_51      -2542.57     993.75  -2.559   0.0337 *
## Week_52       2863.56    1368.12   2.093   0.0697 .
## Week_53      -1253.87     715.14  -1.753   0.1176  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8321 on 8 degrees of freedom
## Multiple R-squared:  0.9006, Adjusted R-squared:  0.242 
## F-statistic: 1.368 on 53 and 8 DF,  p-value: 0.3366

## [1] "Results for crop: Strawberries"
## 
## Call:
## lm(formula = y ~ ., data = x)
## 
## Residuals:
##    Min     1Q Median     3Q    Max 
##  -8816  -2698    765   2981   9094 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -43671.26   62465.98  -0.699   0.5043  
## Week_1         102.83    1116.33   0.092   0.9289  
## Week_2          91.01    1321.97   0.069   0.9468  
## Week_3         977.08    1429.09   0.684   0.5135  
## Week_4         642.01    1189.95   0.540   0.6042  
## Week_5       -1503.25    1357.90  -1.107   0.3005  
## Week_6        1684.53    1832.55   0.919   0.3849  
## Week_7         663.88    1494.57   0.444   0.6687  
## Week_8       -2254.98    2373.98  -0.950   0.3700  
## Week_9        -233.27    1303.06  -0.179   0.8624  
## Week_10      -4874.81    2068.33  -2.357   0.0462 *
## Week_11      -3311.42    3203.01  -1.034   0.3314  
## Week_12       2091.01    2078.02   1.006   0.3438  
## Week_13        586.76    3261.13   0.180   0.8617  
## Week_14      -1237.21    4906.13  -0.252   0.8073  
## Week_15       5846.04    2981.16   1.961   0.0855 .
## Week_16       1960.95    1869.74   1.049   0.3249  
## Week_17       4846.62    2048.05   2.366   0.0455 *
## Week_18        -99.77    2195.10  -0.045   0.9649  
## Week_19       2500.27    1867.66   1.339   0.2175  
## Week_20       2429.33    2047.22   1.187   0.2694  
## Week_21      -1966.57    2243.53  -0.877   0.4063  
## Week_22       1595.38    2027.00   0.787   0.4539  
## Week_23      -1397.62    1989.80  -0.702   0.5024  
## Week_24      -3222.90    1740.20  -1.852   0.1012  
## Week_25      -1082.16    2289.96  -0.473   0.6491  
## Week_26       3451.49    2297.59   1.502   0.1714  
## Week_27       1871.65    3283.91   0.570   0.5844  
## Week_28       3016.32    2634.08   1.145   0.2853  
## Week_29      -4239.79    2675.40  -1.585   0.1517  
## Week_30       -730.59    2354.70  -0.310   0.7643  
## Week_31       1496.45    2156.44   0.694   0.5074  
## Week_32       -186.27    1281.96  -0.145   0.8881  
## Week_33      -2601.00    2394.61  -1.086   0.3090  
## Week_34       7501.91    2461.48   3.048   0.0159 *
## Week_35         71.91    1691.26   0.043   0.9671  
## Week_36      -1000.53    2271.31  -0.441   0.6712  
## Week_37      -2196.19    2706.24  -0.812   0.4405  
## Week_38       2494.36    2442.28   1.021   0.3370  
## Week_39      -5213.91    2410.22  -2.163   0.0625 .
## Week_40       3049.40    2113.92   1.443   0.1871  
## Week_41      -4397.99    2487.55  -1.768   0.1150  
## Week_42       1467.46    2480.99   0.591   0.5705  
## Week_43      -1320.41    1936.86  -0.682   0.5147  
## Week_44        -72.22    1441.49  -0.050   0.9613  
## Week_45      -6995.59    2155.30  -3.246   0.0118 *
## Week_46       4763.70    2009.92   2.370   0.0452 *
## Week_47        429.47    1224.80   0.351   0.7349  
## Week_48       -329.09    2106.45  -0.156   0.8797  
## Week_49        128.17    1107.09   0.116   0.9107  
## Week_50        -26.66    1164.52  -0.023   0.9823  
## Week_51       -454.82    1344.54  -0.338   0.7439  
## Week_52       2203.10    1851.06   1.190   0.2681  
## Week_53      -1115.07     967.58  -1.152   0.2824  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 11260 on 8 degrees of freedom
## Multiple R-squared:  0.957,  Adjusted R-squared:  0.6718 
## F-statistic: 3.356 on 53 and 8 DF,  p-value: 0.03649

## # A tibble: 2 × 3
##   Crop_Type Start_Year End_Year
##   <chr>          <int>    <int>
## 1 Barley          1991     2023
## 2 Canola          1991     2023

new crop data

## # A tibble: 13 × 3
##    Crop_Type                             Start_Year End_Year
##    <chr>                                      <dbl>    <dbl>
##  1 Fresh apples [114114111]                    1926     2023
##  2 Fresh blueberries [1141114]                 1926     2023
##  3 Fresh grapes [1141147]                      1926     2023
##  4 Fresh peaches [114114411]                   1926     2023
##  5 Fresh pears [114114211]                     1926     2023
##  6 Fresh plums and prune plums [1141143]       1926     2023
##  7 Fresh raspberries [114111211]               1926     2023
##  8 Fresh strawberries [114111111]              1926     2023
##  9 Fresh nectarines [114114421]                2002     2023
## 10 Fresh apricots [114114431]                  2007     2023
## 11 Fresh cranberries [114111311]               2007     2023
## 12 Fresh sour cherries [114114521]             2007     2023
## 13 Fresh sweet cherries [114114511]            2007     2023